WO2023165495A1 - 一种到达时延的估计方法、装置及通信设备 - Google Patents

一种到达时延的估计方法、装置及通信设备 Download PDF

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WO2023165495A1
WO2023165495A1 PCT/CN2023/078909 CN2023078909W WO2023165495A1 WO 2023165495 A1 WO2023165495 A1 WO 2023165495A1 CN 2023078909 W CN2023078909 W CN 2023078909W WO 2023165495 A1 WO2023165495 A1 WO 2023165495A1
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time
impulse response
domain
domain impulse
path
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PCT/CN2023/078909
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English (en)
French (fr)
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师源谷
张振宇
任斌
达人
孙韶辉
方荣一
于哲
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大唐移动通信设备有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0852—Delays

Definitions

  • the present disclosure relates to the field of communication technologies, and in particular, to a method, device and communication equipment for estimating delay of arrival.
  • the purpose of the present disclosure is to provide a method, device and communication device for estimating the delay of arrival, which solves the problem of high complexity of the delay estimation algorithm in the related art.
  • An embodiment of the present disclosure provides a method for estimating a delay of arrival, including:
  • time-domain sample point of the first path from the first time-domain impulse response; wherein, the time-domain sample point of the first path refers to: corresponding to the first impulse response peak value greater than the first threshold time domain sample points;
  • performing shift processing on the first time-domain impulse response to obtain a second time-domain impulse response includes:
  • the first time-domain impulse response is a first time-domain impulse response normalized based on the maximum value.
  • the acquiring the first time-domain impulse response according to the positioning signal includes:
  • the correlation between the position movement amount of the shift processing and the time-domain sample point of the first path refers to: after the first time-domain impulse response is subjected to the shift processing, all shifted The time-domain sample points of the first path are not negative.
  • performing shift processing on the first time-domain impulse response to obtain a second time-domain impulse response includes:
  • the At least one target time-domain impulse response includes a time-domain impulse response corresponding to the time-domain sample points of the head path;
  • the window function is as follows:
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • h(n)" represents the target corresponding to the nth sample point after windowing processing
  • Time domain impulse response M represents the time domain sample point of the first path
  • Q represents a predetermined value of the length of the first window.
  • time-domain sample points of the first path are calculated by the following formula:
  • P th represents the first threshold of the first time-domain impulse response
  • M is the time-domain sample point of the first path
  • h(n)' represents the normalization process corresponding to the n-th sample point After the first time-domain impulse response.
  • the shifting the target time-domain impulse response in the first window toward a direction smaller than the time-domain position of the target time-domain impulse response includes:
  • the time domain sample point corresponding to the second time domain impulse response is not a negative value.
  • moving all target time-domain impulse responses in the first window toward the first duration in a direction smaller than the time-domain position of the target time-domain impulse responses to obtain the second Time Domain Impulse Response including:
  • the second time-domain impulse response is calculated by the following formula:
  • h(M+i)" represents all target time-domain impulse responses in the first window
  • M represents the time-domain sample points of the first path
  • i represents the time-domain sample points in the first window except the first Other time-domain sample points outside the time-domain sample point of the path
  • h(M-L+i)"' represents the second time-domain impulse response
  • L represents the first duration
  • Q represents the first A predetermined value for the length of the window.
  • performing a spectral peak search on the pseudo-spectral function to obtain a first estimated value of the arrival delay includes:
  • the acquiring the second estimated value of the arrival delay according to the position movement amount and the first estimated value includes:
  • the unit of the position movement amount is the same as that of the first estimated value.
  • An embodiment of the present disclosure provides a communication device, including: a memory, a transceiver, and a processor:
  • the memory is used to store computer programs; the transceiver is used to send and receive data under the control of the processor; the processor is used to read the computer programs in the memory and perform the following operations:
  • time-domain sample point of the first path from the first time-domain impulse response; wherein, the time-domain sample point of the first path refers to: corresponding to the first impulse response peak value greater than the first threshold time domain sample points;
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the first time-domain impulse response is a first time-domain impulse response normalized based on the maximum value.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the correlation between the position movement amount of the shift processing and the time-domain sample point of the first path refers to: after the first time-domain impulse response is subjected to the shift processing, all shifted The time-domain sample points of the first path are not negative.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the At least one target time-domain impulse response includes a time-domain impulse response corresponding to the time-domain sample points of the head path;
  • the window function is as follows:
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • h(n)" represents the target corresponding to the nth sample point after windowing processing
  • Time domain impulse response M represents the time domain sample point of the first path
  • Q represents a predetermined value of the length of the first window.
  • time-domain sample points of the first path are calculated by the following formula:
  • P th represents the first threshold of the first time-domain impulse response
  • M is the time-domain sample point of the first path
  • h(n)' represents the normalization process corresponding to the n-th sample point After the first time-domain impulse response.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • time-domain sample point corresponding to the second time-domain impulse response is not a negative value.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the second time-domain impulse response is calculated by the following formula:
  • h(M+i)" represents all target time-domain impulse responses in the first window
  • M represents the time-domain sample points of the first path
  • i represents the time-domain sample points in the first window except the first Other time-domain sample points outside the time-domain sample point of the path
  • h(M-L+i)"' represents the second time-domain impulse response
  • L represents the first duration
  • Q represents the first A predetermined value for the length of the window.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the unit of the position movement amount is the same as that of the first estimated value.
  • An embodiment of the present disclosure provides an apparatus for estimating a delay of arrival, including:
  • the first acquisition unit acquires the first time-domain impulse response according to the positioning signal
  • the second acquiring unit is configured to acquire time-domain sample points of the first path from the first time-domain impulse response; wherein, the time-domain sample points of the first path refer to: the first Time-domain sample points corresponding to impulse response peaks;
  • the first processing unit is configured to perform shift processing on the first time-domain impulse response to obtain a second time-domain impulse response. point correlation;
  • the second processing unit is configured to perform spectral peak search on the pseudo-spectral function according to the second time-domain impulse response to obtain a first estimated value of arrival delay;
  • a third obtaining unit configured to obtain a second estimated value of the arrival time delay according to the position movement amount and the first estimated value.
  • An embodiment of the present disclosure provides a processor-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method for estimating the delay of arrival are implemented.
  • the receiving end after receiving the positioning signal, obtains the first time-domain impulse response of the positioning signal; and obtains the first-path time-domain sample points from the first time-domain impulse response; according to The time-domain sample point shifts the first time-domain impulse response to obtain the second time-domain impulse response; when performing TOA estimation, the second time-domain impulse response is used to search for spectral peaks and then the obtained estimate The value is restored, because the first time-domain impulse response is shifted, the dimension of the Vandermonde matrix is greatly reduced, and the complexity of the calculation process is reduced. After the spectral peak search is completed, the calculation is performed according to the amount of position movement. Then the final estimated TOA value can be output, effectively reducing the complexity of the peak search related TOA measurement algorithm.
  • FIG. 1 shows one of the schematic flow charts of the method for estimating the delay of arrival in an embodiment of the present disclosure
  • FIG. 2 shows a schematic diagram of a time-domain impulse response before shift processing according to an embodiment of the present disclosure
  • FIG. 3 shows a schematic diagram of a time-domain impulse response after shift processing in an embodiment of the present disclosure
  • FIG. 4 shows the second schematic flow diagram of the method for estimating the delay of arrival in an embodiment of the present disclosure
  • FIG. 5 shows the third schematic flow diagram of the method for estimating the delay of arrival in the embodiment of the present disclosure
  • FIG. 6 shows the fourth schematic flow diagram of the method for estimating the delay of arrival in an embodiment of the present disclosure
  • FIG. 7 shows the fifth schematic flow diagram of the method for estimating the delay of arrival in an embodiment of the present disclosure
  • FIG. 8 shows a schematic structural diagram of a device for estimating a delay of arrival according to an embodiment of the present disclosure
  • FIG. 9 shows a structural block diagram of a communication device according to an embodiment of the present disclosure.
  • sequence numbers of the following processes do not mean the order of execution, and the order of execution of the processes should be determined by their functions and internal logic, and should not be implemented in the present disclosure.
  • the implementation of the examples constitutes no limitation.
  • the embodiments of the present disclosure provide a method, device, and communication device for estimating a delay of arrival, which solves the problem of high complexity of a delay estimation algorithm in the related art.
  • an embodiment of the present disclosure provides a method for estimating a delay of arrival, which specifically includes the following steps:
  • Step 101 Obtain a first time-domain impulse response according to the positioning signal
  • the sending end sends the positioning signal to the receiving end, and the receiving end measures the channel impulse response of the received positioning signal to estimate the arrival delay.
  • the sending end and the receiving end may be a terminal or a network side device (such as a base station), for example: the sending end is a terminal, the receiving end is a base station, and the terminal sends a positioning signal to the base station,
  • the positioning signal is for example: Sounding Reference Signal (Sounding Reference Signal, SRS), the base station receives the SRS, measures the impulse response related to the SRS, thereby performing TOA estimation; the transmitting end is the base station, and the receiving end is For the terminal, the base station sends a positioning signal to the terminal.
  • the positioning signal is, for example, a positioning reference signal (Positioning Reference Signal, PRS).
  • PRS Positioning Reference Signal
  • the terminal receives the PRS, measures the impulse response related to the PRS, and performs TOA estimation.
  • the first time-domain impulse response may be one or more time-domain impulse responses related to the positioning signal.
  • Step 102 Obtain the time-domain sample points of the first path from the first time-domain impulse response; wherein, the time-domain sample points of the first path refer to: the first impulse response greater than the first threshold The time-domain sample point corresponding to the peak value.
  • the first path is the first impulse response reaching the peak value.
  • a first threshold is set for the first time-domain impulse response, all first time-domain impulse responses are traversed, and all first time-domain impulse responses are The impulse response is compared with the first threshold to obtain a first peak value greater than the first threshold, and the time domain sample point corresponding to the first peak value is the time domain sample point of the first path.
  • the initial path can be line of sight transmission (Line of sight, LOS) diameter.
  • the receiving end acquires first-path time-domain sample points from the multiple first time-domain impulse responses for shifting the first time-domain impulse responses.
  • the first threshold may be set according to TOA measurement requirements.
  • the position of the head path is related to the dimension of the Vandermonde matrix that needs to be constructed when searching for spectral peaks.
  • Step 103 Perform shift processing on the first time-domain impulse response to obtain a second time-domain impulse response, where the position movement amount of the shift processing is related to the time-domain sample point of the first path;
  • Performing shift processing on the first time-domain impulse response may refer to moving the first time-domain impulse response in a time-domain position, and obtaining a second time-domain impulse response after the movement, and the first time-domain impulse response
  • the second time domain impulse response is only different from the time domain position of the first time domain impulse response, and other relevant parameters are the same.
  • the shifting process may be to move the first time-domain impulse response forward (that is, to a direction smaller than the current time-domain position) by a predetermined time-domain length relative to the current time-domain position.
  • the amount of position shift is related to the time-domain sample point of the head path.
  • Step 104 according to the second time-domain impulse response, perform a spectral peak search on the pseudo-spectral function to obtain a first estimated value of the arrival delay.
  • the obtained spectral peak is is the first estimated value of the arrival delay.
  • Step 105 Acquire a second estimated value of the arrival delay according to the position movement amount and the first estimated value.
  • a final estimated value of the arrival time delay (ie, the second estimated value) is calculated according to the shifted position movement amount and the first estimated value.
  • the position recovery of the first estimated value may be performed according to the position movement amount of the shifting process, and then a real TOA estimated value may be obtained.
  • the receiving end after receiving the positioning signal, obtains the first time-domain impulse response of the positioning signal; and obtains the first-path time-domain sample points from the first time-domain impulse response; according to The time-domain sample point shifts the first time-domain impulse response to obtain the second time-domain impulse response; when performing TOA estimation, the second time-domain impulse response is used to search for spectral peaks and then the obtained estimate Value into line recovery, since the first time-domain impulse response is shifted, the dimension of the Vandermonde matrix is greatly reduced, and the complexity of the calculation process is reduced. After the spectral peak search is completed, the back calculation is performed according to the position movement amount, then The final estimated TOA value can be output, effectively reducing the complexity of the peak search for the TOA measurement algorithm.
  • the first time-domain impulse response is a first time-domain impulse response normalized based on the maximum value.
  • the receiving end when performing TOA estimation, after receiving the positioning signal, the receiving end measures the time-domain impulse response of the positioning signal, and performs normalization processing on the time-domain impulse response.
  • the normalization process can be completed by the following formula:
  • h(n)' represents the first time domain position after normalization processing corresponding to the nth sample point
  • h(n) represents the first time domain position obtained before normalization processing corresponding to the nth sample value point Time Domain Impulse Response.
  • [h(n)] * denotes the conjugate of h(n).
  • the obtaining the first time-domain impulse response according to the positioning signal includes: obtaining the first frequency-domain impulse response of the positioning signal; transforming the first frequency-domain impulse response into the first A time-domain impulse response.
  • the receiving end after receiving the positioning signal, measures the positioning signal to obtain the frequency-domain impulse response vector of the positioning signal, and the frequency-domain impulse response vector can be converted by an inverse discrete Fourier transform (IDFT), A corresponding time-domain impulse response, that is, the first time-domain impulse response is obtained.
  • IDFT inverse discrete Fourier transform
  • OFDM Orthogonal Frequency Division Multiplex
  • y(t) represents the received signal at the receiving end
  • n(t) represents the transmitted signal at the transmitting end
  • n(t) represents additive white Gaussian noise
  • h(t) represents the channel impulse response
  • “*” represents Time-domain convolution processing, where in a multipath environment, h(t) can be expressed as:
  • ⁇ () is the Dirac delta function
  • L P is the number of multipath
  • ⁇ i (t) is the time delay of the i-th multipath
  • ⁇ i (t) represents the complex fading coefficient of the i-th multipath component
  • t represents the receiving moment of the signal.
  • the modulated time-domain OFDM symbol can be expressed as:
  • f c represents the OFDM signal carrier frequency, in Hz; f scs represents the subcarrier spacing, in Hz; k is the number of the current subcarrier; b k represents the modulated signal on the subcarrier.
  • the time-domain signal after OFDM passes through the channel is:
  • w k (t) is the additive white Gaussian noise vector of subcarrier k.
  • H k (t) represents the ideal value vector of the frequency domain impulse response
  • expression of the ideal frequency domain impulse response is:
  • V represents the Vandermonde matrix of time delay
  • ⁇ (t) is the modified channel complex fading coefficient
  • the time delay can be further estimated through a signal estimation algorithm (such as a MUSIC algorithm or a maximum likelihood estimation algorithm).
  • a signal estimation algorithm such as a MUSIC algorithm or a maximum likelihood estimation algorithm.
  • the frequency-domain impulse response of the positioning signal can be obtained according to the above calculation, and the corresponding time-domain impulse response can be obtained by performing IDFT transformation on the frequency-domain impulse response.
  • performing shift processing on the first time-domain impulse response to obtain a second time-domain impulse response includes: shifting the first time-domain impulse response toward The direction of the time-domain position of the first time-domain impulse response is shifted to obtain the second time-domain impulse response.
  • shifting the first time-domain impulse response may refer to: moving the first time-domain impulse response forward relative to the current time-domain position (that is, to a direction smaller than the current time-domain position). If the direction of the domain position moves), then the time domain position of the peak (namely the head path) will be advanced, and the dimension of the Vandermonde matrix that needs to be constructed during the spectral peak search will be reduced, which can reduce the complexity of the peak search for the TOA measurement algorithm.
  • performing shift processing on the first time-domain impulse response to obtain a second time-domain impulse response includes:
  • the At least one target time-domain impulse response includes a time-domain impulse response corresponding to the time-domain sample point of the first path; The direction of the time domain position of the domain impulse response is shifted to obtain the second time domain impulse response.
  • the window function is as follows:
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • h(n)" represents the target corresponding to the nth sample point after windowing processing
  • Time-domain impulse response M represents the time-domain sample point of the first path
  • Q represents the predetermined value of the length of the first window, which can be half of the length of the first window.
  • the value of n is The value range is 1 ⁇ n ⁇ K r , where K r is the number of subcarriers actually occupied by the positioning signal.
  • the length of the first window for window selection processing may be set according to TOA estimation requirements.
  • Q may be half of the length of the first window, and Q may be equal to 1.
  • the windowing process refers to using the set window length to search for relevant impulse responses in the corresponding time domain, the signals of the time domain sample points in the window will be retained, and the rest will be set to zero. The advantage of this method is that it can reduce related noise and multipath related effects.
  • a plurality of target time-domain impulse responses within the first window including the first path can be obtained, and the target time-domain impulse responses are: lie in A first time-domain impulse response within the first window.
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • P th represents the first threshold of the first time-domain impulse response
  • the demand can be estimated according to TOA Setting
  • M is the time-domain sample point of the first path.
  • the first threshold is set on the ordinate, and the value range of the P th is: 0 ⁇ P th ⁇ 1, the 0 ⁇ P th ⁇ 1 may be notified by the network or preset by the receiving end fixed.
  • the first time-domain impulse response peak value greater than the first threshold can be obtained according to the above formula, and the time-domain sample point corresponding to the peak value is the time-domain sample point M of the first path.
  • the shifting process can be performed on the time-domain impulse response in the first window, that is, only the time-domain impulse response in the first window
  • the time-domain impulse response moves toward a direction smaller than the current time-domain position to obtain a second time-domain impulse response.
  • the above-mentioned windowing operation can be used; for the second type of TOA estimation algorithm (such as the MUSIC algorithm), the above-mentioned windowing processing can be skipped. step.
  • the above-mentioned step of performing windowing processing by using a window function may be performed to shift the target time-domain impulse response located in the first window.
  • the windowing step is ignored and all the first time domain The impulse response is shifted.
  • the advantage of the windowing process is that it can reduce related noise and related effects brought by multipath.
  • the correlation between the position movement amount of the shift processing and the time-domain sample point of the first path refers to: after the first time-domain impulse response is subjected to the shift processing, all shifted The time-domain sample points of the first path are not negative.
  • the position of the time-domain sample point of the first path is related to the dimension of the Vandermonde matrix that needs to be constructed when searching for a spectral peak, in order to ensure that the complexity of the delay estimation algorithm is reduced, the time domain of the first path The sample point cannot be negative after being shifted.
  • the shifting the target time-domain impulse response in the first window toward a direction smaller than the time-domain position of the target time-domain impulse response includes:
  • the time domain sample point corresponding to the second time domain impulse response is not a negative value.
  • moving all target time-domain impulse responses in the first window toward the first duration in a direction smaller than the time-domain position of the target time-domain impulse responses to obtain the second Time Domain Impulse Response including:
  • h(M+i)" represents all target time-domain impulse responses in the first window
  • (M+i) represents all time-domain sample points in the first window
  • M represents the The time-domain sample point of the first path
  • i represents other time-domain sample points in the first window except the time-domain sample point of the first path
  • h(M-L+i)"' represents the In the second time-domain impulse response
  • L represents the first duration
  • Q represents a predetermined value of the length of the first window, and in this embodiment, the Q may be half of the length of the first window.
  • the target time-domain impulse responses described in this embodiment are all first time-domain impulse responses normalized based on the maximum value.
  • all time domains within a predetermined time-domain range can be shifted. domain impulse response. For example: if windowing processing is performed when determining the time-domain sample points of the first path, all first time-domain impulse responses in the first window (that is, the target time-domain impulse response ) moves forward the first duration in the time domain, it should be noted that. Each first time-domain impulse response within the first window moves forward by a first duration relative to its current time-domain location.
  • the time domain range for the shift process may be the time domain range corresponding to all the first time domain impulse responses corresponding to the positioning signal, that is, all the first time domain ranges corresponding to the positioning signal
  • the domain impulse response moves forward in the time domain for a first duration, and each first time domain impulse response moves for the first duration relative to its current time domain position.
  • the time domain range corresponding to the first time domain impulse response that needs to be shifted can also be customized.
  • the position movement amount of the shifting process is related to the time-domain sample points of the first path, that is, the first duration is related to the time-domain sample points of the first path.
  • the first time domain impulse After the excitation moves the first duration in a direction smaller than the current time domain position, the shifted time domain sample point of the head path is not a negative value.
  • the windowing process is performed on the first time-domain impulse response before shifting, the first duration needs to satisfy: the target time-domain impulse response in the first window is The second time-domain impulse responses obtained by the shift processing are not negative.
  • Figure 2 is the first time-domain impulse response in the first window before moving, where the first path
  • the time-domain sample point M is the point (31, 1) shown in Figure 2
  • Figure 3 is to move all the first time-domain impulse responses in the first window forward (that is, the direction is smaller than that in Figure 2
  • the direction of the time-domain position of the first time-domain impulse response of the first time-domain impulse response moves) the schematic diagram after the first time length L, after the movement, the second time-domain impulse response corresponding to the first time-domain impulse response is obtained, and the second time-domain
  • the time-domain sample point of the first path corresponding to the impulse response is: M-L, which is the point (10, 1) shown in FIG. 3 .
  • the time-domain sample point M-L of the first path after moving is not a negative value.
  • the predefined parameters that can be configured for the first duration assuming that the time unit of the length of a sample point is T S1 , the time-domain sample points (ie spectral peaks) of the first path shown in Fig. Move to the position where the sample point is at 10T S1 , which is the position shown in Figure 3.
  • This parameter is configurable. 10T S1 is a feasible value, which can be changed to 5T S1 or other values according to the actual situation. It should be noted that, considering the influence of the TA adjustment of the base station on the measurement algorithm, it is not recommended to move to the place where the time domain sample point is 0.
  • the obtained first time-domain impulse response is moved towards a direction smaller than the current time-domain position to obtain the second time-domain impulse response, so that when performing TOA estimation, the spectral peak is searched and then restored, because the peak (that is, the time domain position of the head path) is advanced, and the dimension of the Vandermonde matrix that needs to be constructed during the spectral peak search will be reduced, which can reduce the complexity of the peak search for the TOA measurement algorithm.
  • the performing spectral peak search on the pseudo-spectral function according to the second time-domain impulse response to obtain the first estimated value of the arrival delay includes:
  • FFT transformation is performed on the second time-domain impulse response obtained after the shift, which is transformed into a new frequency-domain impulse response X′′, that is, the second frequency-domain impulse response, which is determined by predetermined
  • An estimation algorithm (such as a maximum likelihood estimation algorithm, a MUSIC algorithm) processes the second frequency-domain impulse response,
  • the spectral peak of the pseudo spectrum is found in the pseudo spectral function, and the value of the spectral peak is the first estimated value, which is TOA1.
  • the spectral peak search is performed on the pseudo-spectral function, and the spectral peak obtained by the spectral peak search is the same time as the first path in the second time-domain impulse response.
  • the estimated value corresponding to the sample point in the domain that is, the sample point in the time domain after moving forward. For example: if windowing is performed on the first time-domain impulse response through a window function, all first time-domain impulse responses in the window corresponding to the windowing process are shifted forward, and a predetermined estimation algorithm is used (such as the maximum likelihood time delay estimation algorithm) process the frequency domain impulse responses corresponding to all the shifted second time domain impulse responses, and perform spectral peak search to obtain the first estimated value.
  • all the first time-domain impulse responses in the time domain can be shifted forward, and a predetermined estimation algorithm (such as the MUSIC algorithm) can be used.
  • a predetermined estimation algorithm such as the MUSIC algorithm
  • the frequency domain impulse responses corresponding to all the shifted second time domain impulse responses are processed, and spectral peak search is performed to obtain the first estimated value.
  • TOA1 The calculation method of TOA1 will be described respectively below by taking the maximum likelihood estimation algorithm and the MUSIC algorithm as examples.
  • Example 1 Assuming that the MUSIC algorithm is used for TOA estimation, then according to the second time-domain impulse response, performing a spectral peak search on the pseudo-spectral function to obtain the first estimated value TOA1 of the arrival delay may include:
  • Step 31 covariance matrix estimation; in actual situations, the covariance matrix R XX of the frequency-domain impulse response estimation vector in the real channel frequency domain cannot be directly obtained, usually in the form of multiple measurements, using the new frequency-domain impulse response Estimated stimulus response value X′′ is used to estimate R XX , and N is the corresponding number of snapshots, then the covariance matrix is as follows:
  • the X can be the frequency-domain impulse response corresponding to the second time-domain impulse response obtained by moving after windowing, or it can be the corresponding frequency-domain impulse response of all time-domain impulse responses without windowing. Frequency Domain Impulse Response.
  • Step 32 eigendecomposition; after obtaining multiple groups of frequency-domain impulse responses, matrix decomposition is performed on the above-mentioned covariance matrix, and a signal characteristic matrix composed of signal eigenvalue vectors and a noise characteristic matrix composed of noise characteristic vectors can be obtained.
  • Step 33 spectral peak search, define the pseudo-spectral function of the MUSIC time-delay algorithm as
  • v( ⁇ ) is the Vandermonde matrix with respect to time delay ⁇
  • () H represents the conjugate transpose.
  • Step 34 by searching for the maximum value of the pseudo-spectral function, the propagation time delay ⁇ , ie TOA1, can be determined.
  • Example 2 Assuming that the maximum likelihood algorithm is used for TOA estimation, then according to the second time-domain impulse response, a spectral peak search is performed on the pseudo-spectral function to obtain the first estimated value TOA1 of the delay of arrival, which may include:
  • Step 41 Based on the maximum likelihood time delay estimation algorithm, the likelihood function of ⁇ can be obtained:
  • this function is the spectral peak function of the maximum likelihood time delay estimation algorithm
  • V represents the Vandermonde matrix about the time delay
  • (V H V) -1 represents the inverse matrix of the matrix V H V.
  • the propagation time delay ⁇ output by step 42 is TOA1.
  • the above-mentioned method for obtaining the first estimated value of the arrival time delay by searching the spectral peak is only an exemplary description, and other algorithms may also be used for calculation, which is not limited here.
  • the acquiring the second estimated value of the arrival delay according to the position movement amount and the first estimated value includes:
  • L is the amount of movement of the position.
  • the position movement amount can be added only after it is unified with the TOA unit.
  • Subtraction processing for example: the basic unit of TOA2 and TOA1 is 1ns, you need to change the unit of L from T S1 to 1ns to get L1, and then you can get the value of TOA2.
  • the receiving end of the present disclosure uses the MUSIC algorithm or the maximum likelihood delay estimation algorithm to process the frequency-domain impulse response vector of the signal, and after searching for the spectral peak of the pseudo-spectral function, the corresponding The estimated initial value of the peak value and time, because the peak value is advanced, the dimension of the Vandermonde matrix is greatly reduced.
  • the time advance value is added to output the estimated TOA value, and then the time domain impulse response can be moved back to previous position.
  • the obtained first time-domain impulse response is moved toward a direction smaller than the current time-domain position, and the TOA measurement algorithm performs spectral peak search and then recovers. Reduce the complexity of the peak search for the TOA measurement algorithm.
  • This method is applicable to both the user equipment (User Equipment, UE) positioning method based on the downlink reference signal and the UE positioning method based on the uplink reference signal.
  • the uplink and downlink procedures are similar, but the sending and receiving ends of the reference signal are different. .
  • the TOA measurement method of the UE of the downlink reference signal it is applicable to both the MUSIC algorithm and the maximum likelihood delay estimation algorithm, both of which need to process the channel frequency domain response estimation vector and perform the spectral peak search operation of the pseudo spectrum .
  • the MUSIC algorithm it is necessary to construct a full-rank covariance matrix, then perform eigenvalue decomposition on the covariance matrix, decompose the matrix into signal subspace and noise subspace, and finally construct the corresponding pseudospectral function to search for the peak of the spectrum, and the searched spectrum
  • the peak is the propagation delay.
  • the time delay estimation algorithm based on maximum likelihood needs to construct the corresponding likelihood function and then search for the spectral peak, and then restore its time to the correct value.
  • the following uses the MUSIC algorithm as an example to introduce a low-complexity TOA measurement solution.
  • a low-complexity TOA measurement scheme based on the MUSIC algorithm including two schemes for downlink and uplink.
  • step 1 sending end, such as base station (Base station, BS) configuration sends traditional PRS, and the configuration information of PRS is reported to positioning server;
  • base station Base station
  • Step 2 The positioning server notifies the receiving end (UE) of the configuration information of the PRS;
  • Step 3 The sending end (BS) sends the PRS according to the configuration information of the PRS;
  • Step 4 The receiving end (UE) receives the PRS according to the given PRS configuration information, and measures the frequency-domain impulse response vector of the positioning signal;
  • Step 5 The receiving end processes the frequency-domain impulse response, converts the frequency-domain signal into a time-domain signal through Inverse Fast Fourier Transform (IFFT) transformation, and obtains the first value greater than the first threshold.
  • IFFT Inverse Fast Fourier Transform
  • the time domain sample point corresponding to the first impulse response peak value, and shift all the time domain impulse responses in the time domain forward, and the first impulse response peak value is moved within 10T S1 .
  • This parameter is configurable, 10T S1 is a feasible value, which can be modified to 5T S1 or other values according to the actual situation; after shifting, the time-domain impulse response obtained after shifting is transformed by Fast Fourier Transform (FFT) is a frequency domain signal.
  • FFT Fast Fourier Transform
  • Step 6 Process the frequency-domain impulse response through the MUSIC algorithm, find the spectral peak of the pseudo-spectrum in the pseudo-spectral function of the MUSIC algorithm, refer to steps 31-34 for details, and do not repeat them here.
  • Step 7 After finding the spectral peak of the pseudo spectrum, restore it according to the previously moved Ts value, and obtain the estimated TOA measurement value.
  • the receiving end reports the TOA measurement result to the positioning server, and the positioning server can traverse all locations, obtain the TOA measurement value set of each base station reference signal corresponding to all locations, and save it; after receiving the measurement result, the positioning server judges the UE according to established rules The most likely location, which is considered the final result of the positioning.
  • step 1 the sending end (UE) configures and sends the SRS signal, and reports the configuration information of the SRS to the positioning server;
  • Step 2 The positioning server notifies the receiving end (BS) of the configuration information of the SRS;
  • Step 3 The sending end (UE) sends the SRS according to the configuration information of the SRS;
  • Step 4 The receiving end (BS) receives the SRS according to the given SRS configuration information, and measures the frequency-domain impulse response vector of the positioning signal;
  • Step 5 The receiving end processes the frequency domain impulse response, converts the frequency domain signal into a time domain signal through IFFT transformation, and obtains the time domain sample point corresponding to the first impulse response peak value greater than the first threshold, And shift the impulse response in the time domain, and move the peak of the first impulse response to within 10T S1 .
  • This parameter is configurable. 10T S1 is a feasible value, which can be modified to 5T S1 or its value according to the actual situation. other values, and then transform the time-domain impulse response obtained after the shift into a frequency-domain signal through FFT transformation.
  • Step 6 Process the frequency-domain impulse response through the MUSIC algorithm, find the spectral peak of the pseudo-spectrum in the pseudo-spectral function of the MUSIC algorithm, refer to steps 31-34 for details, and do not repeat them here.
  • Step 7 After finding the spectral peak of the pseudo spectrum, restore it according to the previously moved Ts value, and obtain the estimated TOA measurement value.
  • the receiving end reports the TOA measurement result to the positioning server, and the positioning server can traverse all locations, obtain the TOA measurement value set of each base station reference signal corresponding to all locations, and save it; after receiving the measurement result, the positioning server judges the UE according to established rules The most likely location, which is considered the final result of the positioning.
  • the low-complexity TOA measurement scheme based on the maximum likelihood time delay estimation algorithm, including two schemes of uplink and downlink respectively.
  • step a the sending end (BS) configures and sends the traditional PRS, and reports the configuration information of the PRS to the positioning server;
  • Step b The positioning server notifies the receiving end (UE) of the configuration information of the PRS;
  • Step c The sending end (BS) sends the PRS according to the configuration information of the PRS;
  • Step d The receiving end (UE) receives the PRS according to the given PRS configuration information, and measures the frequency-domain impulse response vector of the positioning signal;
  • Step e the receiving end processes the frequency-domain impulse response, converts the frequency-domain signal into a time-domain signal through IFFT transformation, and obtains a time-domain sample point corresponding to the first impulse response peak value greater than the first threshold; Based on the time-domain sample point corresponding to the first impulse response peak value, a windowing operation is performed on all time-domain impulse responses, and the time-domain impulse responses in the window are shifted forward in the time domain (that is, toward less than Move in the direction of the current time domain position), move to within 10T S1 , this parameter can be configured, 10T S1 is a feasible value, can be modified to 5T S1 or other values according to the actual situation, and then the time domain impulse response after the shift Perform FFT transform to convert to frequency domain signal.
  • Step f The receiving end processes the frequency-domain impulse response through the maximum likelihood delay estimation algorithm, performs a spectral peak search in the ⁇ likelihood function related to the maximum likelihood delay estimation algorithm, and finds the spectral peak of the pseudo spectrum, see step 41-step 42, which will not be repeated here.
  • Step g After finding the spectral peak of the pseudo-spectrum, restore it according to the previously moved Ts value to obtain an estimated TOA value.
  • the receiving end reports the TOA measurement result to the positioning server, and the positioning server can traverse all locations, obtain the TOA measurement value set of each base station reference signal corresponding to all locations, and save it; after receiving the measurement result, the positioning server judges the UE according to established rules The most likely location, which is considered the final result of the positioning.
  • Step a the sending end (UE) configures and sends the SRS signal, and reports the configuration information of the SRS to the positioning server;
  • Step b The positioning server notifies the receiving end (BS) of the configuration information of the SRS;
  • Step c the sending end (UE) sends the SRS according to the configuration information of the SRS;
  • Step d The receiving end (BS) receives the SRS according to the given SRS configuration information, and measures the frequency-domain impulse response vector of the positioning signal;
  • Step e the receiving end processes the frequency-domain impulse response, converts the frequency-domain signal into a time-domain signal through IFFT transformation, and obtains a time-domain sample point corresponding to the first impulse response peak value greater than the first threshold; Based on the time-domain sample point corresponding to the first impulse response peak value, a windowing operation is performed on all time-domain impulse responses, and the time-domain impulse responses in the window are shifted forward in the time domain (that is, toward less than Move in the direction of the current time domain position), move to within 10T S1 , this parameter is configurable, 10T S1 is a feasible value, it can be modified to 5T S1 or other values according to the actual situation, and then the shifted time domain impulse The response is transformed into a frequency domain signal by FFT transformation.
  • Step f The receiving end processes the frequency-domain impulse response through the maximum likelihood delay estimation algorithm, performs a spectral peak search in the ⁇ likelihood function related to the maximum likelihood delay estimation algorithm, and finds the spectral peak of the pseudo spectrum, see step 41-step 42, which will not be repeated here.
  • Step g After finding the spectral peak of the pseudo-spectrum, restore it according to the previously moved Ts value to obtain an estimated TOA value.
  • the receiving end reports the TOA measurement result to the positioning server, and the positioning server can traverse all locations, obtain the TOA measurement value set of each base station reference signal corresponding to all locations, and save it; after receiving the measurement result, the positioning server judges the UE according to established rules most likely location, the location Considered the final result of targeting.
  • IFFT is performed on the frequency-domain impulse response vector of the received signal to convert it into a time-domain signal, and then the time-domain sample point corresponding to the first peak impulse response in the time domain is obtained , after the obtained time-domain impulse response is moved forward, the obtained spectral peak is restored after the positioning algorithm searches for the peak, so as to reduce the complexity of the peak search for the TOA measurement algorithm.
  • the MUSIC and the maximum likelihood delay estimation algorithm in the related art need to be processed through the frequency domain response vector to obtain the corresponding delay estimate, and the Vandermonde matrix constructed in the algorithm
  • the higher dimensionality of the algorithm itself results in a higher space complexity of the algorithm itself, and it takes longer to search for pseudo peaks, resulting in a higher time and space complexity of the algorithm.
  • the embodiments of the present disclosure further reduce the dimensions of the Vandermonde matrix constructed when searching for relevant peaks by moving the peak forward, thereby reducing the corresponding search time.
  • the time and space complexity of the corresponding algorithm is reduced. At the same time, if the window is used for windowing in the time domain, after the window finds the corresponding impulse response, there is no need to modify the relevant window.
  • the receiving end after receiving the positioning signal, obtains the first time-domain impulse response of the positioning signal; and obtains the first-path time-domain sample points from the first time-domain impulse response; according to The time-domain sample point shifts the first time-domain impulse response to obtain the second time-domain impulse response; when performing TOA estimation, the second time-domain impulse response is used to search for spectral peaks and then the obtained estimate The value is restored, because the first time-domain impulse response is shifted, the dimension of the Vandermonde matrix is greatly reduced, and the complexity of the calculation process is reduced. After the spectral peak search is completed, the calculation is performed according to the amount of position movement. Then the final estimated TOA value can be output, effectively reducing the complexity of the peak search related TOA measurement algorithm.
  • an embodiment of the present disclosure provides an apparatus 800 for estimating a delay of arrival, including:
  • the first acquiring unit 810 is configured to acquire a first time-domain impulse response according to the positioning signal
  • the second acquiring unit 820 is configured to acquire time-domain sample points of the first path from the first time-domain impulse response; wherein, the time-domain sample points of the first path refer to: the first path greater than the first threshold A sample point in the time domain corresponding to the peak value of the impulse response;
  • the first processing unit 830 is configured to perform shift processing on the first time-domain impulse response to obtain a second time-domain impulse response. Value point related;
  • the second processing unit 840 is configured to perform spectral peak search on the pseudo-spectral function according to the second time-domain impulse response to obtain a first estimated value of the arrival delay;
  • the third obtaining unit 850 is configured to obtain a second estimated value of the arrival time delay according to the position movement amount and the first estimated value.
  • performing shift processing on the first time-domain impulse response to obtain a second time-domain impulse response includes:
  • the first time-domain impulse response is a first time-domain impulse response normalized based on the maximum value.
  • the first acquisition unit includes:
  • a first acquisition subunit configured to acquire a first frequency-domain impulse response of the positioning signal
  • a first conversion subunit configured to transform the first frequency-domain impulse response into the first time-domain impulse response.
  • the correlation between the position movement amount of the shift processing and the time-domain sample point of the first path refers to: after the first time-domain impulse response is subjected to the shift processing, all shifted The time-domain sample points of the first path are not negative.
  • the first processing unit includes:
  • the first processing subunit is configured to perform windowing processing on the first time-domain impulse response through a window function based on the time-domain sample points of the head path, to obtain at least one target time-domain within the first window Impulse response; wherein, the at least one target time-domain impulse response includes a time-domain impulse response corresponding to the time-domain sample points of the first path;
  • the second processing subunit performs shift processing on the target time-domain impulse response in the first window toward a direction smaller than the time-domain position of the target time-domain impulse response, to obtain the second time-domain impulse response domain impulse response.
  • the window function is as follows:
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • h(n)" represents the target corresponding to the nth sample point after windowing processing
  • Time domain impulse response M represents the time domain sample point of the first path
  • Q represents a predetermined value of the length of the first window.
  • P th represents the first threshold of the first time-domain impulse response
  • M is the time-domain sample point of the first path
  • h(n)' represents the normalization process corresponding to the n-th sample point After the first time-domain impulse response.
  • the second processing subunit is specifically configured to:
  • the time domain sample point corresponding to the second time domain impulse response is not a negative value.
  • the second processing subunit is specifically configured to:
  • h(M+i)" represents all target time-domain impulse responses in the first window
  • M represents the time-domain sample points of the first path
  • i represents the time-domain sample points in the first window except the first Other time-domain sample points outside the time-domain sample point of the path
  • h(M-L+i)"' represents the second time-domain impulse response
  • L represents the first duration
  • Q represents the first A predetermined value for the length of the window.
  • the second processing unit includes:
  • a second conversion subunit configured to convert the second time-domain impulse response into a second frequency-domain impulse response
  • a first determining subunit configured to determine a pseudo-spectral function according to the second frequency-domain impulse response
  • the third processing subunit is configured to search for a spectral peak of the pseudo spectral function to obtain a spectral peak of the pseudo spectral function, where a value of the spectral peak is the first estimated value of the arrival time delay.
  • the third obtaining unit is specifically configured to: add the position movement amount to the first estimated value to obtain the second estimated value;
  • the unit of the position movement amount is the same as that of the first estimated value.
  • the first time-domain impulse response of the positioning signal is obtained; and the time-domain sample points of the first path are obtained from the first time-domain impulse response; and the first time-domain sample points are obtained according to the time-domain sample points
  • the impulse response in the second time domain is shifted to obtain the second time domain impulse response; when performing TOA estimation, the second time domain impulse response is used to search for the spectral peak and then the estimated value obtained is restored.
  • the time-domain impulse response is shifted, which greatly reduces the dimension of the Vandermonde matrix and reduces the complexity of the calculation process.
  • the spectral peak search is completed, the calculation is performed according to the position movement amount, and the final estimated TOA value can be output. Effectively reduce the complexity of the peak search for the TOA measurement algorithm.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.
  • the integrated unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a processor-readable storage medium.
  • the essence of the technical solution of the present disclosure or the part that contributes to the related technology or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium.
  • a computer device which may be a personal computer, a server, or a network device, etc.
  • a processor processor
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic disk or optical disc and other media that can store program codes. .
  • an embodiment of the present disclosure also provides a communication device.
  • the communication device may be a terminal or a network side device, and the communication device includes: a memory 920, a transceiver 900, and a processor 910;
  • the memory 920 is used to store computer programs; the transceiver 900 is used to send and receive data under the control of the processor; the processor 910 is used to read the computer programs in the memory and execute Do the following:
  • time-domain sample point of the first path from the first time-domain impulse response; wherein, the time-domain sample point of the first path refers to: corresponding to the first impulse response peak value greater than the first threshold time domain sample points;
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the first time-domain impulse response is a first time-domain impulse response normalized based on the maximum value.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the correlation between the position movement amount of the shift processing and the time-domain sample point of the first path refers to: after the first time-domain impulse response is subjected to the shift processing, all shifted The time-domain sample points of the first path are not negative.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the At least one target time-domain impulse response includes a time-domain impulse response corresponding to the time-domain sample points of the head path;
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the window function is as follows:
  • h(n)' represents the normalized first time-domain impulse response corresponding to the nth sample point
  • h(n)" represents the target corresponding to the nth sample point after windowing processing
  • Time domain impulse response M represents the time domain sample point of the first path
  • Q represents a predetermined value of the length of the first window.
  • P th represents the first threshold of the first time-domain impulse response
  • M is the time-domain sample point of the first path
  • h(n)' represents the normalization process corresponding to the n-th sample point After the first time-domain impulse response.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the time domain sample point corresponding to the second time domain impulse response is not a negative value.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • h(M+i)" represents all target time-domain impulse responses in the first window
  • M represents the time-domain sample points of the first path
  • i represents the time-domain sample points in the first window except the first Other time-domain sample points outside the time-domain sample point of the path
  • h(M-L+i)"' represents the second time-domain impulse response
  • L represents the first duration
  • Q represents the first A predetermined value for the length of the window.
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the processor is configured to read a computer program in the memory and perform the following operations:
  • the unit of the position movement amount is the same as that of the first estimated value.
  • the receiving end after receiving the positioning signal, obtains the first time-domain impulse response of the positioning signal; and obtains the first-path time-domain sample points from the first time-domain impulse response; according to The time-domain sample point shifts the first time-domain impulse response to obtain the second time-domain impulse response; when performing TOA estimation, the second time-domain impulse response is used to search for spectral peaks and then the obtained estimate The value is restored, because the first time-domain impulse response is shifted, the dimension of the Vandermonde matrix is greatly reduced, and the complexity of the calculation process is reduced. After the spectral peak search is completed, the calculation is performed according to the amount of position movement. Then the final estimated TOA value can be output, effectively reducing the complexity of the peak search related TOA measurement algorithm.
  • the bus architecture may include any number of interconnected buses and bridges, specifically one or more processors represented by the processor 910 and various circuits of the memory represented by the memory 920 are linked together.
  • the bus architecture can also link together various other circuits such as peripherals, voltage regulators, and power management circuits, etc., which are well known in the art and therefore will not be further described herein.
  • the bus interface provides the interface.
  • Transceiver 900 may be a plurality of elements, including a transmitter and a transceiver, providing a means for communicating with various other devices over a transmission medium.
  • the processor 910 is responsible for managing the bus architecture and general processing, and the memory 920 may store data used by the processor 910 when performing operations.
  • the processor 910 can be a central processing unit (Central Processing Unit, CPU), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a field programmable gate array (Field-Programmable Gate Array, FPGA) or a complex programmable logic device (Complex Programmable Logic Device, CPLD), the processor can also adopt a multi-core architecture.
  • CPU Central Processing Unit
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • CPLD Complex Programmable Logic Device
  • specific embodiments of the present disclosure further provide a processor-readable storage medium, on which a computer program is stored, wherein, when the program is executed by a processor, the steps of the above method for estimating the delay of arrival are implemented. And can achieve the same technical effect, in order to avoid repetition, no more details here.
  • the readable storage medium can be any available medium or data storage device that can be accessed by the processor, including but not limited to magnetic storage (such as floppy disk, hard disk, magnetic tape, magneto-optical disk (Magneto-Optical Disk, MO) etc.) , optical storage (such as compact disc (Compact Disk, CD), digital video disc (Digital Versatile Disc, DVD), Blu-ray Disc (Blu-ray Disc, BD), high-definition universal disc (High-Definition Versatile Disc, HVD), etc.), And semiconductor memory (such as ROM, erasable programmable read-only memory (Erasable Programmable ROM, EPROM), electrically erasable programmable read-only memory (Electrically EPROM, EEPROM), non-volatile memory (NAND FLASH), solid state Hard disk (Solid State Disk or Solid State Drive, SSD)), etc.
  • magnetic storage such as floppy disk, hard disk, magnetic tape, magneto-optical disk (Magne
  • the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Accordingly, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present disclosure may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, optical storage, etc.) having computer-usable program code embodied therein.
  • processor-executable instructions may also be stored in a processor-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, such that the instructions stored in the processor-readable memory produce a manufacturing product, the instruction means implements a flow in the flowchart process or processes and/or a function specified in a block or blocks of a block diagram.
  • processor-executable instructions can also be loaded onto a computer or other programmable data processing device, causing a series of operational steps to be performed on the computer or other programmable device to produce a computer-implemented
  • the executed instructions provide steps for implementing the functions specified in the flow or flows of the flowcharts and/or the block or blocks of the block diagrams.
  • the division of the above modules is only a division of logical functions, and may be fully or partially integrated into a physical entity or physically separated during actual implementation.
  • these modules can all be implemented in the form of calling software through processing elements; they can also be implemented in the form of hardware; some modules can also be implemented in the form of calling software through processing elements, and some modules can be implemented in the form of hardware.
  • the determining module may be a separate processing element, or may be integrated into a certain chip of the above-mentioned device.
  • it may also be stored in the memory of the above-mentioned device in the form of program code, and a certain processing element of the above-mentioned device may Call and execute the functions of the modules identified above.
  • each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or an instruction in the form of software.
  • each module, unit, subunit or submodule may be one or more integrated circuits configured to implement the above method, for example: one or more specific integrated circuits (Application Specific Integrated Circuit, ASIC), or, one or Multiple microprocessors (digital signal processor, DSP), or, one or more field programmable gate arrays (Field Programmable Gate Array, FPGA), etc.
  • ASIC Application Specific Integrated Circuit
  • DSP digital signal processor
  • FPGA Field Programmable Gate Array
  • the processing element may be a general-purpose processor, such as a central processing unit (Central Processing Unit, CPU) or other processors that can call program codes.
  • these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).
  • SOC system-on-a-chip

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Abstract

本公开提供了一种到达时延的估计方法、装置及通信设备。所述方法包括：根据定位信号获取第一时域冲激响应；从所述第一时域冲激响应中获取首径的时域样值点；所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；将第一时域冲激响应进行移位处理，获得第二时域冲激响应，移位处理的位置移动量与所述首径的时域样值点相关；根据第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；根据位置移动量以及第一估计值，获取到达时延的第二估计值。

Description

一种到达时延的估计方法、装置及通信设备
相关申请的交叉引用
本公开主张在2022年03月01日在中国提交的中国专利申请号No.202210195788.0的优先权，其全部内容通过引用包含于此。
技术领域
本公开涉及通信技术领域，尤其涉及一种到达时延的估计方法、装置及通信设备。
背景技术
近年来，接入互联网的设备逐渐增多，基于物联网的各种应用服务为人民生活带来了诸多便利。位置信息是实现这些应用服务的一个重要先决条件。因此，如何实时高效地获得精确的位置信息，已成为推动行业发展中亟待解决的关键问题。相关技术中，不断针对包括到达时延(Time of Arrival，TOA)测量技术在内的定位技术进行广泛的研究，例如多重信号分类算法(Multiple Signal Classification，MUSIC)时延估计算法和最大似然时延估计算法，但是相关技术中的时延估计算法中，均存在着建立伪谱测量时，矩阵维度过高的问题，导致算法复杂度较高。
发明内容
本公开的目的在于提供一种到达时延的估计方法、装置及通信设备，解决了相关技术中的时延估计算法的复杂度较高的问题。
本公开的实施例提供一种到达时延的估计方法，包括：
根据定位信号获取第一时域冲激响应；
从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
可选地，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
可选地，所述根据定位信号获取第一时域冲激响应，包括：
获取定位信号的第一频域冲激响应；
将所述第一频域冲激响应变换为所述第一时域冲激响应。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
可选地，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述窗函数如下：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
可选地，所述首径的时域样值点通过如下公式计算：
M＝arg minn|h(n)′|2>Pth
其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
可选地，所述将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，包括：
根据所述首径的时域样值点确定所述位置移动量为第一时长；
将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
其中，所述第二时域冲激响应对应的时域样值点不为负值。
可选地，所述将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应，包括：
通过如下公式计算所述第二时域冲激响应：
h(M-L+i)″′＝h(M+i)″   -Q≤i≤Q
其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
可选地，所述根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值，包括：
将所述第二时域冲激响应转换为第二频域冲激响应；
根据所述第二频域冲激响应确定伪谱函数；
对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
可选地，所述根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值，包括：
将所述位置移动量与所述第一估计值相加，获得所述第二估计值；
其中，所述位置移动量与所述第一估计值的单位相同。
本公开的实施例提供一种通信设备，包括：存储器，收发机，处理器：
存储器，用于存储计算机程序；收发机，用于在所述处理器的控制下收发数据；处理器，用于读取所述存储器中的计算机程序并执行以下操作：
根据定位信号获取第一时域冲激响应；
从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
获取定位信号的第一频域冲激响应；
将所述第一频域冲激响应变换为所述第一时域冲激响应。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述窗函数如下：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
可选地，所述首径的时域样值点通过如下公式计算：
M＝arg minn|h(n)′|2>Pth
其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
根据所述首径的时域样值点确定所述位置移动量为第一时长；
将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
其中，第二时域冲激响应对应的时域样值点不为负值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
通过如下公式计算所述第二时域冲激响应：
h(M-L+i)″′＝h(M+i)″   -Q≤i≤Q
其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述第二时域冲激响应转换为第二频域冲激响应；
根据所述第二频域冲激响应确定伪谱函数；
对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述位置移动量与所述第一估计值相加，获得所述第二估计值；
其中，所述位置移动量与所述第一估计值的单位相同。
本公开的实施例提供一种到达时延的估计装置，包括：
第一获取单元，根据定位信号获取第一时域冲激响应；
第二获取单元，用于从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
第一处理单元，用于将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
第二处理单元，用于根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
第三获取单元，用于根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
本公开的实施例提供一种处理器可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现上述的到达时延的估计方法的步骤。
本公开的上述技术方案的有益效果是：
本公开的实施例，接收端在接收到定位信号后，获取定位信号的第一时域冲激响应；并从所述第一时域冲激响应中获取首径的时域样值点；根据时域样值点将第一时域冲激响应进行移位处理，获得第二时域冲激响应；在进行TOA估计时利用第二时域冲激响应进行谱峰搜索后再对获得的估计值进行恢复，由于对所述第一时域冲激响应进行移位处理，大大减少了范德蒙矩阵的维度，减小运算过程的复杂度，谱峰搜索完成之后根据位置移动量进行回退计算，则可以输出最终估计的TOA值，有效减小有关TOA测量算法的峰值搜索时的复杂度。
附图说明
图1表示本公开实施例的到达时延的估计方法的流程示意图之一；
图2表示本公开实施例进行移位处理前的时域冲激响应示意图；
图3表示本公开实施例进行移位处理后的时域冲激响应示意图；
图4表示本公开实施例的到达时延的估计方法的流程示意图之二；
图5表示本公开实施例的到达时延的估计方法的流程示意图之三；
图6表示本公开实施例的到达时延的估计方法的流程示意图之四；
图7表示本公开实施例的到达时延的估计方法的流程示意图之五；
图8表示本公开实施例的到达时延的估计装置的结构示意图；
图9表示本公开实施例通信设备的结构框图。
具体实施方式
为使本公开要解决的技术问题、技术方案和优点更加清楚，下面将结合附图及具体实施例进行详细描述。在下面的描述中，提供诸如具体的配置和组件的特定细节仅仅是为了帮助全面理解本公开的实施例。因此，本领域技术人员应该清楚，可以对这里描述的实施例进行各种改变和修改而不脱离本公开的范围和精神。另外，为了清楚和简洁，省略了对已知功能和构造的描述。
应理解，说明书通篇中提到的“一个实施例”或“一实施例”意味着与实施例有关的特定特征、结构或特性包括在本公开的至少一个实施例中。因此，在整个说明书各处出现的“在一个实施例中”或“在一实施例中”未必一定指相同的实施例。此外，这些特定的特征、结构或特性可以任意适合的方式结合在一个或多个实施例中。
在本公开的各种实施例中，应理解，下述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本公开实施例的实施过程构成任何限定。
本公开实施例中术语“和/或”，描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。字符“/”一般表示前后关联对象是一种“或”的关 系。
本公开实施例中术语“多个”是指两个或两个以上，其它量词与之类似。
下面将结合本公开实施例中的附图，对本公开实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本公开一部分实施例，并不是全部的实施例。基于本公开中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本公开保护的范围。
具体地，本公开的实施例提供了一种到达时延的估计方法、装置及通信设备，解决了相关技术中的时延估计算法的复杂度较高的问题。
如图1所示，本公开的实施例提供了一种到达时延的估计方法，具体包括以下步骤：
步骤101、根据定位信号获取第一时域冲激响应；
该实施例中，发送端向接收端发送定位信号，所述接收端测量接收的定位信号的信道冲激响应，进行达到时延估计。其中，所述发送端和所述接收端可以为终端也可以为网络侧设备(例如基站)，例如：所述发送端为终端，所述接收端为基站，所述终端向基站发送定位信号，所述定位信号例如：探测参考信号(Sounding Reference Signal，SRS)，所述基站接收所述SRS，测量有关SRS的冲激响应，从而进行TOA估计；所述发送端为基站，所述接收端为终端，所述基站向终端发送定位信号，所述定位信号例如：定位参考信号(Positioning Reference Signal，PRS)，所述终端接收所述PRS，测量有关PRS的冲激响应，从而进行TOA估计。
所述第一时域冲激响应可以为所述定位信号相关的一个或者多个时域冲激响应。
步骤102、从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点。
所述首径即第一个到达峰值的冲激响应，在该实施例中，为第一时域冲激响应设置第一门限，遍历所有第一时域冲激响应，将所有第一时域冲激响应与第一门限比较，获得大于所述第一门限的第一个峰值，该第一个峰值对应的时域样值点即为所述首径的时域样值点。该首径可以为视线传输(Line of  sight，LOS)径。所述接收端从多个第一时域冲激响应中获取首径的时域样值点，用于对第一时域冲激响应进行移位。所述第一门限可以根据TOA测量需求设置。
其中，所述首径的位置与谱峰搜索时需要构造的范德蒙矩阵的维度有关。
步骤103、将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；。
对所述第一时域冲激响应进行移位处理，可以是指将所述第一时域冲激响应在时域位置上进行移动，移动后获得第二时域冲激响应，所述第二时域冲激响应仅与所述第一时域冲激响应的时域位置不同，其他相关参数相同。
可选地，所述移位处理可以是将所述第一时域冲激响应相对于当前的时域位置，向前(即向小于当前时域位置的方向)移动预定时域长度。可选地，在对所述第一时域冲激响应进行移位时，位置移动量与首径的时域样值点相关。
步骤104、根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值。
对所述第一时域冲激响应移位后获得第二时域冲激响应，通过伪谱函数对所述第二时域冲激响应进行处理，并进行谱峰搜索，获得的谱峰即为所述到达时延的第一估计值。
步骤105、根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
由于所述第一估计值是对第一时域冲激响应移位处理后计算获得的，因此该第一估计值不准确。根据所述移位处理的位置移动量和所述第一估计值，计算所述到达时延的最终估计值(即所述第二估计值)。可选地，可以根据所述移位处理的位置移动量，对所述第一估计值进行位置恢复，则可以获得真实的TOA估计值。
本公开的实施例，接收端在接收到定位信号后，获取定位信号的第一时域冲激响应；并从所述第一时域冲激响应中获取首径的时域样值点；根据时域样值点将第一时域冲激响应进行移位处理，获得第二时域冲激响应；在进行TOA估计时利用第二时域冲激响应进行谱峰搜索后再对获得的估计值进 行恢复，由于对所述第一时域冲激响应进行移位处理，大大减少了范德蒙矩阵的维度，减小运算过程的复杂度，谱峰搜索完成之后根据位置移动量进行回退计算，则可以输出最终估计的TOA值，有效减小有关TOA测量算法的峰值搜索时的复杂度。
可选地，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
该实施例中，在进行TOA估计时，接收端接收到所述定位信号后，测量定位信号的时域冲激响应，并对时域冲激响应进行归一化处理。所述归一化处理可以通过如下公式完成：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域位置；h(n)表示第n个样值点对应的归一化处理前获得的第一时域冲激响应。[h(n)]*表示h(n)的共轭。
作为一个可选实施例，所述根据定位信号获取第一时域冲激响应，包括：获取定位信号的第一频域冲激响应；将所述第一频域冲激响应变换为所述第一时域冲激响应。
该实施例中，接收端接收定位信号后，测量定位信号获得有关定位信号的频域冲激响应矢量，可以通过离散傅里叶逆变换(IDFT)将所述频域冲激响应矢量进行转换，获得对应的时域冲激响应，即所述第一时域冲激响应。下面对获得频域冲激响应的方法进行举例说明。
可选地，本公开实施例采用的信号模型可以为正交频分复用(Orthogonal Frequency Division Multiplex，OFDM)无线通信信号，接收信号如下式所示：
y(t)＝h(t)*s(t)+n(t)
其中，y(t)表示所述接收端的接收信号，n(t)表示发送端的发送信号，n(t)表示加性的高斯白噪声，h(t)表示信道冲激响应，“*”表示时域卷积处理，其中在多径环境下，h(t)可以表示为：
其中，δ()为Dirac delta函数，LP为多径的个数，τi(t)是第i条多径的时延；αi(t)表示第i条多径分量的复衰落系数，t表示信号的接收时刻。
在含有K个子载波的OFDM***中，调制后的时域OFDM符号可以表示为：
其中，fc表示OFDM信号载波频率，单位为Hz；fscs表示子载波间隔，单位为Hz；k是当前子载波的编号；bk表示子载波上调制的信号。
根据上述公式可得OFDM经过信道后的时域信号为：
其中，wk(t)为子载波k的加性高斯白噪声矢量。
上述接收信号y(t)经过快速傅里叶变换(FFT)变换后，第k个子载波上的频域冲激响应估计值为：
其中，Hk(t)表示频域冲激响应的理想值矢量，则理想的频域冲激响应的表达式为：
则频域冲激响应的矢量形式可以表示为：
x(t)＝H(y)+w(t)＝Vα(t)+w(t)
V表示时延的范德蒙矩阵，α(t)为修正信道复衰落系数。
根据上述计算，可以通过信号估计算法(例如MUSIC算法或最大似然估计算法)对时延进行进一步的估计。本公开实施例的分析中认为在若干个OFDM符号内，无线信道是半静态的(semi-static channel)，因此，忽略下标t。
根据上述计算可以获得定位信号的频域冲激响应，通过对所述频域冲激响应进行IDFT变换可以获得对应的时域冲激响应。
作为一个可选实施例，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
该实施例中，对所述第一时域冲激响应进行移位可以是指：将所述第一时域冲激响应相对于当前的时域位置向前移动(即朝向小于所述当前时域位置的方向移动)，则峰值(即首径)的时域位置提前，在谱峰搜索时需要构造的范德蒙矩阵的维度会减小，可以减小有关TOA测量算法峰值搜索时的复杂度。
作为一个可选实施例，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述窗函数如下：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值，可以为所述第一窗口长度的一半。可选地，n的取值范围为1≤n≤Kr，其中，Kr为所述定位信号实际占用的子载波个数。
该实施例中，进行取窗处理的所述第一窗口的长度可以根据TOA估计需求设置。其中，Q可以为第一窗口长度的一半，Q可以等于1。所述取窗处理是指利用设定好的窗长来搜索相应的时域的上的有关冲激响应，在窗口内的时域样值点的信号会被保留，其余的会被置零，该方法优点是可以降低有关噪声和多径带来的相关影响。
围绕所述首径的时域样值点进行取窗处理，可以获得包括所述首径在内的位于第一窗口内的多个目标时域冲激响应，所述目标时域冲激响应为位于 所述第一窗口内的第一时域冲激响应。在该第一窗口内该大于第一门限的第一个峰值对应的第一时域冲激响应的时域样值点，即所述首径的时域样值点。
可选地，所述首径的时域样值点通过如下公式计算：
M＝arg minn|h(n)′|2>Pth
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，Pth表示第一时域冲激响应的第一门限，可以根据TOA估计需求设置；M为所述首径的时域样值点。如图2所示，所述第一门限设置于纵坐标，所述Pth的取值范围为：0<Pth<1，该0<Pth<1可以是网络通知的或者接收端预先设定的。
该实施例中，如上述公式可以获得大于第一门限的第一个时域冲激响应峰值，该峰值对应的时域样值点即所述首径的时域样值点M。
该实施例中，对所述第一时域冲激响应进行取窗处理后，可以针对所述第一窗口内的时域冲激响应进行移位处理，即只将所述第一窗口内的时域冲激响应朝向小于当前时域位置的方向移动，获得第二时域冲激响应。
需要说明的是，针对第一类TOA估计算法(例如最大似然时延算法)可以使用上述取窗处理的操作；针对第二类TOA估计算法(如MUSIC算法)可以跳过上述取窗处理的步骤。例如：在通过最大似然时延算法进行TOA估计时，可以执行上述通过窗函数进行取窗处理的步骤，将位于第一窗口内的目标时域冲激响应进行移位。若使用MUSIC算法进行TOA估计，为了避免影响到MUSIC计算过程中的特征值分解构建出的噪声子空间影响到时延估计的准确性，则忽略该取窗步骤，直接将所有的第一时域冲激响应进行移位处理。所述取窗处理的优点是可以降低有关噪声和多径带来的相关影响。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。该实施例中，由于所述首径的时域样值点的位置与谱峰搜索时需要构造的范德蒙矩阵的维度相关，为了保证减小时延估计算法的复杂度，所述首径的时域样值点经过移位后不能为负值。
可选地，所述将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，包括：
根据所述首径的时域样值点确定所述位置移动量为第一时长；
将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
其中，所述第二时域冲激响应对应的时域样值点不为负值。
可选地，所述将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应，包括：
通过如下公式计算所述第二时域冲激响应：
h(M-L+i)″′＝h(M+i)″   -Q≤i≤Q
其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应，(M+i)表示所述第一窗口内的所有的时域样值点；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值，该实施例中，所述Q可以为所述第一窗口的长度的一半。可选地，该实施例中所述的目标时域冲激响应均为基于最大值归一化处理后的第一时域冲激响应。
该实施例中，在对所述第一时域冲激响应进行移位时，为了避免只移动一个冲激响应对TOA估计算法的测量值造成影响，可以移动一个预定时域范围内的所有时域冲激响应。例如：若在确定所述首径的时域样值点时进行了取窗处理，则可以将所述第一窗口内的所有第一时域冲激响应(即所述目标时域冲激响应)在时域上向前移动第一时长，需要说明的是。第一窗口内的每个第一时域冲激响应均相对于自身当前的时域位于向前移动第一时长。若未进行取窗处理，则进行移位处理的时域范围可以为所述定位信号对应的所有的第一时域冲激响应对应的时域范围，即将所述定位信号对应的所有第一时域冲激响应在时域上向前移动第一时长，且每个第一时域冲激响应相对于自身当前的时域位置移动第一时长。需要进行移位处理的第一时域冲激响应对应的时域范围也可以自定义。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关，即所述第一时长与所述首径的时域样值点相关。该实施例中，所述第一时域冲 激响朝向小于当前时域位置的方向移动所述第一时长后，移位后的所述首径的时域样值点不为负值。在该实施例中，由于在移位前对所述第一时域冲激响应进行了取窗处理，则所述第一时长需要满足：所述第一窗口内的目标时域冲激响应进行移位处理获得的第二时域冲激响应，均不为负值。
下面对所述移位处理进行说明。以对所述第一时域冲激响应进行了取窗处理为例，如图2和图3所示，图2为移动前的第一窗口内的第一时域冲激响应，其中首径的时域样值点M即为图2中所示的(31，1)的点；图3为将第一窗口内的第一时域冲激响应全部向前移动(即朝向小于图2中的第一时域冲激响应的时域位置的方向移动)第一时长L后的示意图，移动后获得与第一时域冲激响应对应的第二时域冲激响应，该第二时域冲激响应对应的首径的时域样值点为：M-L，即为图3中所示的(10，1)的点。移动后的所述首径的时域样值点M-L不为负值。
其中，第一时长时可以配置的预定义参数，假设一个样值点长度的时间单位为TS1，将图2所示的首径的时域样值点(即谱峰)在时域上向前移动到样值点在10TS1的位置，即图3所示的位置。该参数可配置，10TS1为一个可行的值，可根据实际情况修改为5TS1或其他值。需要说明的是，考虑到基站的TA调整对测量算法的影响，不推荐移动到时域样值点为0处。
该实施例中，对获得的第一时域冲激响应朝向小于当前时域位置的方向移动后获得第二时域冲激响应，这样在进行TOA估计时进行谱峰搜索后再恢复，由于峰值(即首径)的时域位置提前，则在谱峰搜索时需要构造的范德蒙矩阵的维度会减小，可以减小有关TOA测量算法峰值搜索时的复杂度。
作为一个可选实施例，所述根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值，包括：
将所述第二时域冲激响应转换为第二频域冲激响应；根据所述第二频域冲激响应确定伪谱函数；对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
该实施例中，对移位后获得的所述第二时域冲激响应进行FFT变换，这转换为新的频域冲激响应X″，即所述第二频域冲激响应，通过预定估计算法(例如最大似然估计算法、MUSIC算法)对所述第二频域冲激响应进行处理， 在伪谱函数找到伪谱的谱峰，该谱峰的值即为所述第一估计值，即为TOA1。
需要说明的是，在根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，所述谱峰搜索获得的谱峰是与第二时域冲激响应中的首径的时域样值点(即向前移动后的时域样值点)对应的估计值。例如：若通过窗函数对所述第一时域冲激响应进行取窗处理，将所取窗处理对应的窗口内的所有第一时域冲激响应进行向前移位，并利用预定估计算法(如最大似然时延估计算法)对移位后的所有第二时域冲激响应对应的频域冲激响应进行处理，并进行谱峰搜索获得所述第一估计值。若获得所述首径的时域样值点时未进行取窗处理，则可以将时域上的所有第一时域冲激响应进行向前移位，并利用预定估计算法(如MUSIC算法)对移位后的所有第二时域冲激响应对应的频域冲激响应进行处理，并进行谱峰搜索获得所述第一估计值。
下面以最大似然估计算法、MUSIC算法为例分别说明TOA1的计算方法。
示例一：假设采用MUSIC算法进行TOA估计，则所述根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值TOA1，可以包括：
步骤31、协方差矩阵估计；在实际情况中，真实的信道频域下频域冲激响应估计矢量的协方差矩阵RXX无法直接获得，通常采用多次测量的形式，利用新的频域冲激响应估计值X″对RXX进行估计，N为相应的快拍数，则协方差矩阵如下：
需要说明的是，该X″可以是取窗处理后移动获得的第二时域冲激响对应的频域冲激响应，也可以是未取窗情况下所有时域冲激响应移动后对应的频域冲激响应。
步骤32、特征分解；在得到多组的频域冲激响应后，对上述协方差矩阵进行矩阵分解，可获得由信号特征值向量组成的信号特征矩阵和噪声特征向量组成的噪声特征矩阵，特征分解过程如下：
RXX＝US∧SUS H+UN∧NUN H
其中，对角矩阵为 US表示由信号特征矢量构成的信号特征矩阵UN表示由噪声特征矢量构成的噪声特征矩阵
步骤33、谱峰搜索，定义MUSIC时延算法的伪谱函数为
其中，v(τ)时关于时延τ的范德蒙矩阵，()H表示共轭转置。
步骤34、通过搜索伪谱函数的最大值即可确定传播时延τ，即TOA1。
示例二：假设采用最大似然算法进行TOA估计，则根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值TOA1，可以包括：
步骤41、基于最大似然时延估计算法，可得τ的似然函数：
L(τ)＝X″(t)HV(VHV)-1VHX″(t)
其中，该函数即为最大似然时延估计算法的谱峰函数，V表示关于时延的范德蒙矩阵， (VHV)-1表示矩阵VHV的逆矩阵。
步骤42、对上述最大似然函数进行谱峰搜索，多径时延下的算法时延τ可以化简为：
τ＝arg max{L(τ)}
其中，步骤42输出的传播时延τ即TOA1。
需要说明的是，上述谱峰搜索获得到达时延的第一估计值的方法仅为示例性说明，还可以利用其它算法计算，在此不做限定。
作为一个可选实施例，所述根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值，包括：
将所述位置移动量与所述第一估计值相加，获得所述第二估计值；其中，所述位置移动量与所述第一估计值的单位相同。
该实施例中，在获得所述第一估计值后，按照前面移位处理的位置移动量，对获得的所述第一估计值进行恢复，可以获得恢复后的时延估计值TOA2＝TOA1+L。L为所述位置移动量。
其中，需要说明的是，位置移动量与所述TOA单位统一后才可以进行加 减处理，例如：TOA2和TOA1的基本单位都是1ns，需要先将L的单位从TS1转为1ns，得到L1，才能得到TOA2的值。
本公开的接收端在接收到定位信号时，采用MUSIC算法或最大似然时延估计算法，对信号的频域冲激响应矢量进行处理，进行伪谱函数的谱峰的搜索后，会得到相应的峰值和时间的估计初值，因为峰值提前，大大减少了范德蒙矩阵的维度，谱峰搜索完成之后加上时间提前量，就可以输出估计的TOA值，之后可将时域冲激响应移回之前的位置。
本公开的实施例通过获得首径的时域样值点，对获得的第一时域冲激响应朝向小于当前时域位置的方向移动，在TOA测量算法进行谱峰搜索后再进行恢复，来减小有关TOA测量算法峰值搜索时的复杂度。该方法既适用于基于下行链路参考信号的用户设备(User Equipment，UE)定位方法又适用于基于上行链路参考信号的UE定位方法，上下行流程类似，只是参考信号的发送和接收端不同。
对于下行链路参考信号的UE的TOA测量方法，既适用于MUSIC算法又适用最大似然时延估计算法，两者都需要对信道频域响应估计矢量进行处理，进行伪谱的谱峰搜索操作。对于MUSIC算法需要构建满秩的协方差矩阵，然后对协方差矩阵进行特征值分解，将该矩阵分解为信号子空间和噪声子空间，最后构建相应的伪谱函数搜索谱峰值，搜索到的谱峰值即为传播时延。而基于最大似然的时延估计算法需要构造相应的似然函数再进行谱峰搜索，之后再将其时间恢复为正确值。下面以MUSIC算法为例，介绍低复杂度TOA测量方案。
一、基于MUSIC算法的低复杂度TOA测量方案，包括下行和上行两个方案分别说明。
(一)下行：以下行为例。采用MUSIC算法进行下行链路参考信号的TOA估计时，低复杂度TOA测量方案定位方法流程如图4所示：
其中步骤1：发送端，如基站(Base station，BS)配置发送传统的PRS，并将PRS的配置信息上报定位服务器；
步骤2：定位服务器将PRS的配置信息通知接收端(UE)；
步骤3：发送端(BS)按照PRS的配置信息发送PRS；
步骤4：接收端(UE)按照所给的PRS的配置信息接收PRS，测得有关定位信号的频域冲激响应矢量；
步骤5：接收端对频域冲激响应进行处理，通过快速傅里叶逆变换(Inverse Fast Fourier Transform，IFFT)变换将频域信号转变为时域信号，取得大于所述第一门限的第一个冲激响应峰值对应的时域样值点，并将时域上的所有时域冲激响应进行向前移位，第一个冲激响应峰值移动到10TS1以内，该参数可配置，10TS1为一个可行的值，可根据实际情况修改为5TS1或其他值；移位处理后，将移位后获得的时域冲激响应进行快速傅里叶变换(Fast Fourier Transform，FFT)变换转换为频域信号。
步骤6：通过MUSIC算法对频域冲激响应进行处理，在MUSIC算法的伪谱函数，找到伪谱的谱峰，具体参照步骤31-步骤34，在此不做赘述。
步骤7：在找到伪谱的谱峰后，按照之前移动的Ts值，对其进行恢复，获得估计的TOA测量值。
接收端将TOA测量结果上报给定位服务器，定位服务器可以遍历所有位置，求得所有位置对应的各个基站参考信号的TOA测量值集合，并保存；定位服务器接收到测量结果后，按既定法则判定UE最有可能的位置，该位置视为定位的最终结果。
(二)上行：以上行为例。采用MUSIC算法进行下行链路参考信号的TOA估计时，低复杂度TOA测量方案定位方法流程如图5所示。
其中步骤1：发送端(UE)配置发送SRS信号，并将SRS的配置信息上报定位服务器；
步骤2：定位服务器将SRS的配置信息通知接收端(BS)；
步骤3：发送端(UE)按照SRS的配置信息发送SRS；
步骤4：接收端(BS)按照所给的SRS的配置信息接收SRS，测得有关定位信号的频域冲激响应矢量；
步骤5：接收端对频域冲激响应进行处理，通过IFFT变换将频域信号转变为时域信号，取得大于所述第一门限的第一个冲激响应峰值对应的时域样值点，并将时域上的冲激响应进行移位，第一个冲激响应峰值移动到10TS1以内，该参数可配置，10TS1为一个可行的值，可根据实际情况修改为5TS1或其 他值，再将移位后获得的时域冲激响应进行FFT变换转换为频域信号。
步骤6：通过MUSIC算法对频域冲激响应进行处理，在MUSIC算法的伪谱函数，找到伪谱的谱峰，具体参照步骤31-步骤34，在此不做赘述。
步骤7：在找到伪谱的谱峰后，根据之前移动的Ts值，对其进行恢复，获得估计的TOA测量值。
接收端将TOA测量结果上报给定位服务器，定位服务器可以遍历所有位置，求得所有位置对应的各个基站参考信号的TOA测量值集合，并保存；定位服务器接收到测量结果后，按既定法则判定UE最有可能的位置，该位置视为定位的最终结果。
二、基于最大似然时延估计算法的低复杂度TOA测量方案，包括上行和下行两个方案分别说明。
(A)以下行为例：采用最大似然时延估计算法进行下行链路参考信号的TOA估计时，低复杂度TOA测量方案定位方法流程如图6所示。
其中步骤a：发送端(BS)配置发送传统的PRS，并将PRS的配置信息上报定位服务器；
步骤b：定位服务器将PRS的配置信息通知接收端(UE)；
步骤c：发送端(BS)按照PRS的配置信息发送PRS；
步骤d：接收端(UE)按照所给的PRS的配置信息接收PRS，测得有关定位信号的频域冲激响应矢量；
步骤e：接收端对频域冲激响应进行处理，通过IFFT变换将频域信号转变为时域信号，取得大于所述第一门限的第一个冲激响应峰值对应的时域样值点；基于该第一个冲激响应峰值对应的时域样值点，对所有时域冲激响应进行取窗操作，并将窗口内时域冲激响应在时域上向前移位(即朝向小于当前时域位置的方向移动)，移动到10TS1以内，该参数可配置，10TS1为一个可行的值，可根据实际情况修改为5TS1或其他值，再将移动后的时域冲激响应进行FFT变换转换为频域信号。
步骤f：接收端通过最大似然时延估计算法对频域冲激响应进行处理，在最大似然时延估计算法有关τ似然函数中进行谱峰搜索，找到伪谱的谱峰，参见步骤41-步骤42，在此不做赘述。
步骤g：在找到伪谱的谱峰后，按照之前移动的Ts值，对其进行恢复，获得估计的TOA值。
接收端将TOA测量结果上报给定位服务器，定位服务器可以遍历所有位置，求得所有位置对应的各个基站参考信号的TOA测量值集合，并保存；定位服务器接收到测量结果后，按既定法则判定UE最有可能的位置，该位置视为定位的最终结果。
(B)上行：以上行为例。采用最大似然时延估计算法进行下行链路参考信号的TOA估计时，低复杂度TOA测量方案定位方法流程如图7所示。
其中步骤a：发送端(UE)配置发送SRS信号，并将SRS的配置信息上报定位服务器；
步骤b：定位服务器将SRS的配置信息通知接收端(BS)；
步骤c：发送端(UE)按照SRS的配置信息发送SRS；
步骤d：接收端(BS)按照所给的SRS的配置信息接收SRS，测得有关定位信号的频域冲激响应矢量；
步骤e：接收端对频域冲激响应进行处理，通过IFFT变换将频域信号转变为时域信号，取得大于所述第一门限的第一个冲激响应峰值对应的时域样值点；基于该第一个冲激响应峰值对应的时域样值点，对所有时域冲激响应进行取窗操作，并将窗口内时域冲激响应在时域上向前移位(即朝向小于当前时域位置的方向移动)，移动到10TS1以内，该参数可配置，10TS1为一个可行的值，可根据实际情况修改为5TS1或其他值，再将移位后的时域冲激响应进行FFT变换转换为频域信号。
步骤f：接收端通过最大似然时延估计算法对频域冲激响应进行处理，在最大似然时延估计算法有关τ似然函数中进行谱峰搜索，找到伪谱的谱峰，参见步骤41-步骤42，在此不做赘述。
步骤g：在找到伪谱的谱峰后，按照之前移动的Ts值，对其进行恢复，获得估计的TOA值。
接收端将TOA测量结果上报给定位服务器，定位服务器可以遍历所有位置，求得所有位置对应的各个基站参考信号的TOA测量值集合，并保存；定位服务器接收到测量结果后，按既定法则判定UE最有可能的位置，该位置 视为定位的最终结果。
本公开的实施例，首先对接收信号的频域冲激响应矢量，进行IFFT变换，将其转变为时域信号，再获得时域上的第一个峰值冲激响应对应的时域样值点，对获得的时域冲激响应向前移动后，在定位算法进行谱峰搜索后再对获得的谱峰进行恢复，来减小有关TOA测量算法峰值搜索时的复杂度。相比于相关技术中的的算法，相关技术中的MUSIC和最大似然时延估计算法，都需要通过频域响应矢量进行处理，来获得相应的时延估计值，而算法中构造的范德蒙矩阵的维度较高造成算法本身的空间复杂度较高，伪峰谱峰搜索时花费时间较长，造成算法的时间和空间复杂度均较高。本公开实施例为了进一步减小有关谱峰搜索时的算法复杂度，通过将峰值前移的方式，进一步减小有关峰值的进行搜索时构造的范德蒙矩阵维度，减小了相应的搜索时间，对相应算法的时间空间复杂度都进行了降低。同时若使用窗口进行时域的取窗处理，则窗口在找到相应冲击响应后，不需要再对有关窗口进行任何修改。
本公开的实施例，接收端在接收到定位信号后，获取定位信号的第一时域冲激响应；并从所述第一时域冲激响应中获取首径的时域样值点；根据时域样值点将第一时域冲激响应进行移位处理，获得第二时域冲激响应；在进行TOA估计时利用第二时域冲激响应进行谱峰搜索后再对获得的估计值进行恢复，由于对所述第一时域冲激响应进行移位处理，大大减少了范德蒙矩阵的维度，减小运算过程的复杂度，谱峰搜索完成之后根据位置移动量进行回退计算，则可以输出最终估计的TOA值，有效减小有关TOA测量算法的峰值搜索时的复杂度。
以上实施例就本公开的到达时延的估计方法做出介绍，下面本实施例将结合附图对其对应的装置做进一步说明。
具体地，如图8所示，本公开实施例提供一种到达时延的估计装置800，包括：
第一获取单元810，根据定位信号获取第一时域冲激响应；
第二获取单元820，用于从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
第一处理单元830，用于将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
第二处理单元840，用于根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
第三获取单元850，用于根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
可选地，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
可选地，所述第一获取单元包括：
第一获取子单元，用于获取定位信号的第一频域冲激响应；
第一转换子单元，用于将所述第一频域冲激响应变换为所述第一时域冲激响应。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
可选地，所述第一处理单元包括：
第一处理子单元，用于基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
第二处理子单元，将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述窗函数如下：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
可选地，所述首径的时域样值点通过如下公式计算：
M＝arg minn|h(n)′|2>Pth
其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
可选地，所述第二处理子单元具体用于：
根据所述首径的时域样值点确定所述位置移动量为第一时长；
将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
其中，所述第二时域冲激响应对应的时域样值点不为负值。
可选地，所述第二处理子单元具体用于：
通过如下公式计算所述第二时域冲激响应：
h(M-L+i)″′＝h(M+i)″   -Q≤i≤Q
其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
可选地，所述第二处理单元包括：
第二转换子单元，用于将所述第二时域冲激响应转换为第二频域冲激响应；
第一确定子单元，用于根据所述第二频域冲激响应确定伪谱函数；
第三处理子单元，用于对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
可选地，所述第三获取单元具体用于：将所述位置移动量与所述第一估计值相加，获得所述第二估计值；
其中，所述位置移动量与所述第一估计值的单位相同。
本公开的实施例，获取定位信号的第一时域冲激响应；并从所述第一时域冲激响应中获取首径的时域样值点；根据时域样值点将第一时域冲激响应进行移位处理，获得第二时域冲激响应；在进行TOA估计时利用第二时域冲激响应进行谱峰搜索后再对获得的估计值进行恢复，由于对所述第一时域冲激响应进行移位处理，大大减少了范德蒙矩阵的维度，减小运算过程的复杂度，谱峰搜索完成之后根据位置移动量进行回退计算，则可以输出最终估计的TOA值，有效减小有关TOA测量算法的峰值搜索时的复杂度。
在此需要说明的是，本公开实施例提供的上述装置，能够实现上述方法实施例所实现的所有方法步骤，且能够达到相同的技术效果，在此不再对本实施例中与方法实施例相同的部分及有益效果进行具体赘述。
需要说明的是，本公开实施例中对单元的划分是示意性的，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式。另外，在本公开各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个处理器可读取存储介质中。基于这样的理解，本公开的技术方案本质上或者说对相关技术做出贡献的部分或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)或处理器(processor)执行本公开各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
如图9所示，本公开实施例还提供一种通信设备，所述通信设备可以为终端也可以为网络侧设备，所述通信设备包括：存储器920，收发机900，处理器910；
存储器920，用于存储计算机程序；收发机900，用于在所述处理器的控制下收发数据；处理器910，用于读取所述存储器中的计算机程序并执行以 下操作：
根据定位信号获取第一时域冲激响应；
从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
获取定位信号的第一频域冲激响应；
将所述第一频域冲激响应变换为所述第一时域冲激响应。
可选地，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲 激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
所述窗函数如下：
其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
可选地，所述首径的时域样值点通过如下公式计算：
M＝arg minn|h(n)′|2>Pth
其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
根据所述首径的时域样值点确定所述位置移动量为第一时长；
将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
其中，所述第二时域冲激响应对应的时域样值点不为负值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
通过如下公式计算所述第二时域冲激响应：
h(M-L+i)″′＝h(M+i)″   -Q≤i≤Q
其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述第二时域冲激响应转换为第二频域冲激响应；
根据所述第二频域冲激响应确定伪谱函数；
对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
可选地，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
将所述位置移动量与所述第一估计值相加，获得所述第二估计值；
其中，所述位置移动量与所述第一估计值的单位相同。
本公开的实施例，接收端在接收到定位信号后，获取定位信号的第一时域冲激响应；并从所述第一时域冲激响应中获取首径的时域样值点；根据时域样值点将第一时域冲激响应进行移位处理，获得第二时域冲激响应；在进行TOA估计时利用第二时域冲激响应进行谱峰搜索后再对获得的估计值进行恢复，由于对所述第一时域冲激响应进行移位处理，大大减少了范德蒙矩阵的维度，减小运算过程的复杂度，谱峰搜索完成之后根据位置移动量进行回退计算，则可以输出最终估计的TOA值，有效减小有关TOA测量算法的峰值搜索时的复杂度。
其中，在图9中，总线架构可以包括任意数量的互联的总线和桥，具体由处理器910代表的一个或多个处理器和存储器920代表的存储器的各种电路链接在一起。总线架构还可以将诸如***设备、稳压器和功率管理电路等之类的各种其他电路链接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口提供接口。收发机900可以是多个元件，即包括发送机和收发机，提供用于在传输介质上与各种其他装置通信的单元。处理器910负责管理总线架构和通常的处理，存储器920可以存储处理器910在执行操作时所使用的数据。
处理器910可以是中央处理器(Central Processing Unit，CPU)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现场可编程门阵列(Field－Programmable Gate Array，FPGA)或复杂可编程逻辑器件(Complex Programmable Logic Device，CPLD)，处理器也可以采用多核架构。
在此需要说明的是，本公开实施例提供的上述通信设备，能够实现上述方法实施例所实现的所有方法步骤，且能够达到相同的技术效果，在此不再 对本实施例中与方法实施例相同的部分及有益效果进行具体赘述。
另外，本公开具体实施例还提供一种处理器可读存储介质，其上存储有计算机程序，其中，该程序被处理器执行时实现如上述到达时延的估计方法的步骤。且能达到相同的技术效果，为避免重复，这里不再赘述。其中，所述可读存储介质可以是处理器能够存取的任何可用介质或数据存储设备，包括但不限于磁性存储器(例如软盘、硬盘、磁带、磁光盘(Magneto-Optical Disk，MO)等)、光学存储器(例如光盘(Compact Disk，CD)、数字视频光盘(Digital Versatile Disc，DVD)、蓝光光碟(Blu-ray Disc，BD)、高清通用光盘(High-Definition Versatile Disc，HVD)等)、以及半导体存储器(例如ROM、可擦除可编程只读存储器(Erasable Programmable ROM，EPROM)、电可擦除可编程只读存储器(Electrically EPROM，EEPROM)、非易失性存储器(NAND FLASH)、固态硬盘(Solid State Disk或Solid State Drive，SSD))等。
本领域内的技术人员应明白，本公开的实施例可提供为方法、***、或计算机程序产品。因此，本公开可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本公开可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器和光学存储器等)上实施的计算机程序产品的形式。
本公开是参照根据本公开实施例的方法、设备(***)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机可执行指令实现流程图和/或方框图中的每一个流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机可执行指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理设备的处理器执行的指令产生用于实现在流程图中的一个流程或多个流程和/或方框图中的一个方框或多个方框中指定的功能的装置。
这些处理器可执行指令也可存储在能引导计算机或其他可编程数据处理设备以特定方式工作的处理器可读存储器中，使得存储在该处理器可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图的一个流 程或多个流程和/或方框图的一个方框或多个方框中指定的功能。
这些处理器可执行指令也可装载到计算机或其他可编程数据处理设备上，使得在计算机或其他可编程设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程设备上执行的指令提供用于实现在流程图的一个流程或多个流程和/或方框图的一个方框或多个方框中指定的功能的步骤。
需要说明的是，应理解以上各个模块的划分仅仅是一种逻辑功能的划分，实际实现时可以全部或部分集成到一个物理实体上，也可以物理上分开。且这些模块可以全部以软件通过处理元件调用的形式实现；也可以全部以硬件的形式实现；还可以部分模块通过处理元件调用软件的形式实现，部分模块通过硬件的形式实现。例如，确定模块可以为单独设立的处理元件，也可以集成在上述装置的某一个芯片中实现，此外，也可以以程序代码的形式存储于上述装置的存储器中，由上述装置的某一个处理元件调用并执行以上确定模块的功能。其它模块的实现与之类似。此外这些模块全部或部分可以集成在一起，也可以独立实现。这里所述的处理元件可以是一种集成电路，具有信号的处理能力。在实现过程中，上述方法的各步骤或以上各个模块可以通过处理器元件中的硬件的集成逻辑电路或者软件形式的指令完成。
例如，各个模块、单元、子单元或子模块可以是被配置成实施以上方法的一个或多个集成电路，例如：一个或多个特定集成电路(Application Specific Integrated Circuit，ASIC)，或，一个或多个微处理器(digital signal processor，DSP)，或，一个或者多个现场可编程门阵列(Field Programmable Gate Array，FPGA)等。再如，当以上某个模块通过处理元件调度程序代码的形式实现时，该处理元件可以是通用处理器，例如中央处理器(Central Processing Unit，CPU)或其它可以调用程序代码的处理器。再如，这些模块可以集成在一起，以片上***(system-on-a-chip，SOC)的形式实现。
本公开的说明书和权利要求书中的术语“第一”、“第二”等是用于区别类似的对象，而不必用于描述特定的顺序或先后次序。应该理解这样使用的数据在适当情况下可以互换，以便这里描述的本公开的实施例，例如除了在这里图示或描述的那些以外的顺序实施。此外，术语“包括”和“具有”以 及他们的任何变形，意图在于覆盖不排他的包含，例如，包含了一系列步骤或单元的过程、方法、***、产品或设备不必限于清楚地列出的那些步骤或单元，而是可包括没有清楚地列出的或对于这些过程、方法、产品或设备固有的其它步骤或单元。此外，说明书以及权利要求中使用“和/或”表示所连接对象的至少其中之一，例如A和/或B和/或C，表示包含单独A，单独B，单独C，以及A和B都存在，B和C都存在，A和C都存在，以及A、B和C都存在的7种情况。类似地，本说明书以及权利要求中使用“A和B中的至少一个”应理解为“单独A，单独B，或A和B都存在”。
显然，本领域的技术人员可以对本公开进行各种改动和变型而不脱离本公开的精神和范围。这样，倘若本公开的这些修改和变型属于本公开权利要求及其等同技术的范围之内，则本公开也意图包含这些改动和变型在内。

Claims (23)

  1. 一种到达时延的估计方法，包括：
    根据定位信号获取第一时域冲激响应；
    从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
    将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
    根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
    根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
  2. 根据权利要求1所述的方法，其中，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
    将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
  3. 根据权利要求1所述的方法，其中，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
  4. 根据权利要求1所述的方法，其中，所述根据定位信号获取第一时域冲激响应，包括：
    获取定位信号的第一频域冲激响应；
    将所述第一频域冲激响应变换为所述第一时域冲激响应。
  5. 根据权利要求1所述的方法，其中，所述移位处理的位置移动量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
  6. 根据权利要求1所述的方法，其中，所述将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，包括：
    基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述 至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
    将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
  7. 根据权利要求6所述的方法，其中，所述窗函数如下：
    其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
  8. 根据权利要求1或6所述的方法，其中，所述首径的时域样值点通过如下公式计算：
    M＝arg minn|h(n)′|2>Pth
    其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
  9. 根据权利要求6所述的方法，其中，所述将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，包括：
    根据所述首径的时域样值点确定所述位置移动量为第一时长；
    将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
    其中，所述第二时域冲激响应对应的时域样值点不为负值。
  10. 根据权利要求9所述的方法，其中，所述将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应，包括：
    通过如下公式计算所述第二时域冲激响应：
    h(M-L+i)″′＝h(M+i)″  -Q≤i≤Q
    其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
  11. 根据权利要求1所述的方法，其中，所述根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值，包括：
    将所述第二时域冲激响应转换为第二频域冲激响应；
    根据所述第二频域冲激响应确定伪谱函数；
    对所述伪谱函数进行谱峰搜索，获得所述伪谱函数的谱峰，所述谱峰的值为所述到达时延的第一估计值。
  12. 一种通信设备，包括：存储器，收发机，处理器：
    存储器，用于存储计算机程序；收发机，用于在所述处理器的控制下收发数据；处理器，用于读取所述存储器中的计算机程序并执行以下操作：
    根据定位信号获取第一时域冲激响应；
    从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
    将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
    根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
    根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
  13. 根据权利要求12所述的通信设备，其中，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
    将所述第一时域冲激响应朝向小于所述第一时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
  14. 根据权利要求12所述的通信设备，其中，所述第一时域冲激响应为基于最大值归一化处理后的第一时域冲激响应。
  15. 根据权利要求12所述的通信设备，其中，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
    获取定位信号的第一频域冲激响应；
    将所述第一频域冲激响应变换为所述第一时域冲激响应。
  16. 根据权利要求12所述的通信设备，其中，所述移位处理的位置移动 量与所述首径的时域样值点相关是指：所述第一时域冲激响应进行所述移位处理后，移位后的所述首径的时域样值点不为负值。
  17. 根据权利要求12所述的通信设备，其中，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
    基于所述首径的时域样值点，通过窗函数对所述第一时域冲激响应进行取窗处理，获得位于第一窗口内的至少一个目标时域冲激响应；其中，所述至少一个目标时域冲激响应包括所述首径的时域样值点对应的时域冲激响应；
    将所述第一窗口内的所述目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向进行移位处理，获得所述第二时域冲激响应。
  18. 根据权利要求17所述的通信设备，其中，
    所述窗函数如下：
    其中，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应，h(n)″表示取窗处理后的第n个样值点对应的目标时域冲激响应，M表示所述首径的时域样值点，Q表示所述第一窗口的长度的预定值。
  19. 根据权利要求12或17所述的通信设备，其中，所述首径的时域样值点通过如下公式计算：
    M＝arg minn|h(n)′|2>Pth
    其中，Pth表示所述第一时域冲激响应的第一门限，M为所述首径的时域样值点，h(n)′表示第n个样值点对应的归一化处理后的第一时域冲激响应。
  20. 根据权利要求17所述的通信设备，其中，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
    根据所述首径的时域样值点确定所述位置移动量为第一时长；
    将所述第一窗口内的所有目标时域冲激响应，朝向小于所述目标时域冲激响应的时域位置的方向移动所述第一时长，获得所述第二时域冲激响应；
    其中，所述第二时域冲激响应对应的时域样值点不为负值。
  21. 根据权利要求20所述的通信设备，其中，所述处理器用于读取所述存储器中的计算机程序并执行以下操作：
    通过如下公式计算所述第二时域冲激响应：
    h(M-L+i)″′＝h(M+i)″  -Q≤i≤Q
    其中，h(M+i)″表示所述第一窗口内的所有目标时域冲激响应；M表示所述首径的时域样值点，i表示所述第一窗口内除所述首径的时域样值点外的其他时域样值点；h(M-L+i)″′表示所述第二时域冲激响应，L表示所述第一时长；Q表示所述第一窗口的长度的预定值。
  22. 一种到达时延的估计装置，包括：
    第一获取单元，根据定位信号获取第一时域冲激响应；
    第二获取单元，用于从所述第一时域冲激响应中获取首径的时域样值点；其中，所述首径的时域样值点是指：大于第一门限的第一个冲激响应峰值对应的时域样值点；
    第一处理单元，用于将所述第一时域冲激响应进行移位处理，获得第二时域冲激响应，所述移位处理的位置移动量与所述首径的时域样值点相关；
    第二处理单元，用于根据所述第二时域冲激响应，对伪谱函数进行谱峰搜索，获得到达时延的第一估计值；
    第三获取单元，用于根据所述位置移动量以及所述第一估计值，获取所述到达时延的第二估计值。
  23. 一种处理器可读存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如权利要求1至11中任一项所述的到达时延的估计方法的步骤。
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