CN116256738B - Sine frequency modulation signal detection method and device under large Doppler condition - Google Patents
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Abstract
A sine frequency modulation signal detection method and device under a large Doppler condition belong to the field of underwater sound signal processing. The problem that the detector in the prior art can detect the sinusoidal frequency modulation signal only after requiring the priori known frequency modulation parameters of the sinusoidal frequency modulation signal is solved. The method of the invention comprises the following steps: step 1, carrying out narrow-band filtering on a received signal; step 2, performing Hilbert transform on the signal subjected to the narrow-band filtering in the step 1, and estimating the instantaneous frequency of the signal; step 3, performing differential calculation on the instantaneous frequency obtained by the calculation in the step 2 to obtain an instantaneous frequency differential sequence; step 4, further calculating and obtaining a variance sequence of the envelope of the instantaneous frequency differential sequence by using the result of the step 3; and 5, judging whether the signal exists or not by taking the variance sequence of the envelope in the step 4 as a detection statistic. The invention is mainly applied to the field of underwater acoustic signal processing.
Description
Technical Field
The invention belongs to the field of underwater acoustic signal processing.
Background
The sinusoidal frequency modulation signal is used as a commonly used sonar signal form, has the advantages of simplicity, flexibility, strong reverberation resistance and the like, and is widely applied to the fields of underwater target detection, underwater sound positioning and the like. Because the underwater sound velocity is low, when a larger radial velocity exists between the receiving platform and the transmitting platform, a large Doppler effect is introduced, so that a receiving signal has obvious Doppler mismatch problem, and the signal detection performance is seriously affected. Therefore, the problem of sinusoidal frequency modulation signal detection under the condition of large Doppler is always a hot spot problem in the field of underwater acoustic signal processing.
The matched filtering method is an optimal detector for confirming a signal under the maximum criterion of the output signal-to-noise ratio in a white noise background, but the detector has adaptability only to signal amplitude change and delay change and has weak adaptability to Doppler frequency shift, namely, the detection performance of the detector can be seriously reduced under the condition of large Doppler frequency shift. In 1995, liang Guolong proposed a signal detection theory based on transient parameter statistical characteristics, and constructed an instantaneous frequency variance detector for a single-frequency pulse (CW) signal, which has the advantages of small operand and stable performance, successfully solves the technical problems of channel leakage resistance, reverberation interference resistance and the like in multichannel CW signal detection, but is only applicable to CW signals or signals with extremely narrow bandwidth. In 2007, the detection thought of an instantaneous frequency variance detector is taken as a reference, and the characteristic parameters of the instantaneous invariance of the frequency modulation signal are obtained by carrying out proper conversion on the instantaneous frequency, so that the frequency modulation slope variance detector and the periodic slope variance detector are provided, and good Doppler mismatch resistance is shown, but the two detectors are respectively applicable to the linear frequency modulation signal and the hyperbolic frequency modulation signal. For other frequency-modulated signals such as sinusoidal frequency-modulated signals, instantaneous frequency mean square error detectors have been proposed by the applicant, but the detector requires that the frequency-modulated parameters of sinusoidal frequency-modulated signals are known a priori, which needs to be solved.
Disclosure of Invention
The invention aims to solve the problem that a detector in the prior art can detect sinusoidal frequency modulation signals only when the frequency modulation parameters of the sinusoidal frequency modulation signals are known a priori; the invention provides a sine frequency modulation signal detection method under a large Doppler condition. The large Doppler condition refers to the condition that a large radial velocity exists between a receiving platform and a transmitting platform, and the radial velocity is more than 10m/s, and the large Doppler condition is called.
The sine frequency modulation signal detection method under the condition of large Doppler comprises the following steps:
step 1, carrying out narrow-band filtering on echo signals received by a receiving platform;
step 2, hilbert transformation is carried out on the signals subjected to the narrow-band filtration in the step 1, and the instantaneous frequency of each moment of the signals subjected to the narrow-band filtration is estimated;
step 3, obtaining an instantaneous frequency differential sequence of each moment by carrying out differential calculation on the instantaneous frequency of each moment;
step 4, calculating and obtaining the envelope of the instantaneous frequency differential sequence of each moment in the period of the echo signal according to the instantaneous frequency differential sequence of each moment, and calculating the variance sequence value of the envelope of each moment according to the envelope of the instantaneous frequency differential sequence of each moment;
step 5, comparing the variance sequence value of the envelope at each moment with a threshold TH as a detection statistic; and when the value is smaller than the threshold TH, determining that the sinusoidal frequency modulation signal exists in the echo signal, otherwise, determining that the sinusoidal frequency modulation signal does not exist in the echo signal.
Preferably, in step 1, the narrow-band filtering of the echo signal is implemented by using an FIR band-pass filter.
Preferably, in step 2, the expression of the instantaneous frequency at each time is:
where f (k) is the instantaneous frequency of the narrowband filtered signal at the kth sampling instant, k is the sequence number of the sampling instant, τ is the sampling interval,for the phase of the echo signal after the narrowband filtering at the kth sampling instant, +>The phase of the filtered echo signal is narrowband for the (k+1) th sample time.
It is preferred that the composition of the present invention,
where x (k) is the narrowband filtered signal at the kth sample time,the imaginary part of the signal after the hilbert transform is x (k).
Preferably, in step 3, the expression of the instantaneous frequency differential sequence at each moment is:
wherein g 1 (k) For the k-th sampling instant instantaneous frequency differential sequence, f (k) is the k-th sampling instant instantaneous frequency, f (k+1) is the k+1-th sampling instant instantaneous frequency, τ is the sampling interval, and k is the sampling instant sequence number.
Preferably, in step 4, the implementation manner of calculating the envelope of the instantaneous frequency differential sequence at each time in the period where the echo signal is located according to the instantaneous frequency differential sequence at each time is as follows:
step 41, for each moment of instant frequency difference sequence g 1 (k) Doing the following stepsTo obtain a phase-shifted signal g 2 (k) The method comprises the steps of carrying out a first treatment on the surface of the k is the serial number of the sampling time;
step 42, utilizing g 2 (k) And g is equal to 1 (k) An envelope a (k) of the instantaneous frequency difference sequence at each instant is obtained.
It is preferred that the composition of the present invention,
preferably, in step 4, the implementation manner of calculating the variance sequence value of the envelope at each time is as follows:
calculating variance of envelope A (k) of instantaneous frequency difference sequence at each moment to obtain variance sequence value of envelope at each moment
Wherein,
a (k) is the envelope of the k-th sampling instant instantaneous frequency differential sequence, A (k+i) is the envelope of the k+i-th sampling instant instantaneous frequency differential sequence, i is the sum variable, D [ A (k) ]]Is the variance of a (k), M is the sliding window length,the envelope average value of all instantaneous frequency difference sequences in the window from the kth to the Mth sampling time.
The sinusoidal frequency modulation signal detection device under the large Doppler condition comprises a storage device, a processor and a computer program which is stored in the storage device and can run on the processor, wherein the processor executes the computer program to realize the sinusoidal frequency modulation signal detection method under the large Doppler condition.
The beneficial effects brought by the invention are as follows:
aiming at the characteristics of sinusoidal frequency modulation signals, the invention provides a sinusoidal frequency modulation signal detection method under a large Doppler condition. The threshold TH is determined by adopting a constant false alarm detection criterion, namely, determining the threshold according to the false alarm probability under the noise condition.
The detection of the sine frequency modulation signal can be realized without priori knowing specific parameters of the sine frequency modulation signal; the detection performance of the invention is not affected by Doppler, and the invention has good adaptability to high-speed movement of the target. And the verification proves that the method has good robustness to the large Doppler condition.
Drawings
Fig. 1 is a flowchart of the implementation of the sinusoidal frequency modulation signal detection method under the condition of large doppler.
FIG. 2 is a graph of probability density distribution of detection statistics (variance of instantaneous frequency differential sequence envelope) under different conditions; wherein, the reference sign A1 is the probability density distribution diagram of the detection statistic under the condition of 0dB, the reference sign A2 is the probability density distribution diagram of the detection statistic under the condition of-5 dB, the reference sign A3 is the probability density distribution diagram of the detection statistic under the condition of-10 dB, and the reference sign A4 is the probability density distribution diagram of the detection statistic under the condition of pure noise; the abscissa z represents the detection statistic, and the ordinate p (z) represents the probability density varying with z; FIG. 3 is a waveform diagram of an echo signal;
FIG. 4 is a graph of detection statistics (i.e., variance sequence of the envelope of the instantaneous frequency difference sequence) versus a threshold;
FIG. 5 is a graph showing the comparison of detection performance of the detection device of the present invention and the conventional matched filter. Wherein reference numeral B1 denotes an operating characteristic obtained with the detection device of the present invention at a target radial velocity of 15m/s, reference numeral B2 denotes an operating characteristic obtained with the existing matched filter at a target radial velocity of 15m/s, reference numeral B3 denotes an operating characteristic obtained with the detection device of the present invention at a target radial velocity of 25m/s, reference numeral B4 denotes an operating characteristic obtained with the existing matched filter at a target radial velocity of 25m/s, reference numeral B5 denotes an operating characteristic obtained with the detection device of the present invention at a target radial velocity of 35m/s, reference numeral B6 denotes an operating characteristic obtained with the existing matched filter at a target radial velocity of 35m/s, and SNR is a signal-to-noise ratio.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
Example 1:
referring to fig. 1, a sinusoidal fm signal detection method under the large doppler condition described in embodiment 1 is described, and the method includes the following steps:
step 1, carrying out narrow-band filtering on echo signals received by a receiving platform;
step 2, hilbert transformation is carried out on the signals subjected to the narrow-band filtration in the step 1, and the instantaneous frequency of each moment of the signals subjected to the narrow-band filtration is estimated;
step 3, obtaining an instantaneous frequency differential sequence of each moment by carrying out differential calculation on the instantaneous frequency of each moment;
step 4, calculating and obtaining the envelope of the instantaneous frequency differential sequence of each moment in the period of the echo signal according to the instantaneous frequency differential sequence of each moment, and calculating the variance sequence value of the envelope of each moment according to the envelope of the instantaneous frequency differential sequence of each moment;
step 5, comparing the variance sequence value of the envelope at each moment with a threshold TH as a detection statistic; and when the value is smaller than the threshold TH, determining that the sinusoidal frequency modulation signal exists in the echo signal, otherwise, determining that the sinusoidal frequency modulation signal does not exist in the echo signal.
The method is mainly used for checking the echo signals reflected by the target and judging whether sinusoidal frequency modulation signals exist in the echo signals or not; and for sinusoidal frequency modulated signals, the complex expression can be written as:
x(t)＝Aexp[j2πf c t+jm f sin(2πf m t)] (1)；
in the formula (1), T is continuous time, T is more than 0 and less than T, A is amplitude of sine frequency modulation signal, f c For carrier frequency, f m For modulating frequency, m f For the modulation index, T is the signal pulse width.
The waveform of the echo signal changes due to the relative motion of the transceiver platform, and the waveform is represented by frequency shift, namely Doppler phenomenon.
If the target approaches the sonar system, the target movement speed v is a positive number. Defining pulse width compression parameters as follows:
where c is the speed of sound. Assuming that the initial distance of the target is d 0 The echo signal is:
wherein,
in equation 4, τ 0 Is propagation delay;
substituting equations 1, 2 and 4 into equation 3, the expression for obtaining the echo signal is:
therefore, the invention can effectively detect the sinusoidal frequency modulation signal carried in the echo signal shown in the formula 5, namely can accurately detect whether the sinusoidal frequency modulation signal exists or not in the echo signal shown in the formula 5,
in step 1, the narrow-band filtering of the echo signal is implemented by using an FIR band-pass filter. The purpose is to suppress out-of-band noise and improve the signal-to-noise ratio.
Further, in step 2, the transient frequency is estimated for the narrowband filtered signal of step 1 using a hilbert transform. The specific principle is as follows:
the instantaneous frequency principle of estimating an arbitrary continuous-time sinusoidal frequency modulated signal x (t) by hilbert is as follows:
hilbert transform of x (t)The method comprises the following steps:
x (t) andforming a pair of complex conjugate pairs to obtain an analytic signal z (t),
wherein X (t) is the amplitude of the analytic signal z (t),to resolve the phase of signal z (t), t is a continuous time, and
thus, the instantaneous frequency f (t) is obtained as:
discretizing equation 9, the instantaneous frequency calculation of the estimated signal in digital signal processing is:
thus, in step 2, the expression of the instantaneous frequency at each instant is:
where f (k) is the instantaneous frequency of the narrowband filtered signal at the kth sampling instant, k is the sequence number of the sampling instant, τ is the sampling interval,for the phase of the echo signal after the narrowband filtering at the kth sampling instant, +>The phase of the filtered echo signal is narrowband for the (k+1) th sample time.
Still further, the method comprises the steps of,wherein x (k) is the narrowband filtered signal at the kth sample instant, +.>The imaginary part of the signal after the hilbert transform is x (k). In step 3, differential calculation is performed on the instantaneous frequency at each moment to achieve the purpose of removing the center frequency, and a differential sequence of the instantaneous frequency is obtained, namely
Wherein g 1 (k) For the k-th sampling instant instantaneous frequency differential sequence, f (k) is the k-th sampling instant instantaneous frequency, f (k+1) is the k+1-th sampling instant instantaneous frequency, τ is the sampling interval, and k is the sampling instant sequence number.
Further, in step 4, the envelope of the instantaneous frequency differential sequence of each moment in the period of the echo signal is obtained according to the calculation of the instantaneous frequency differential sequence of each moment, and the implementation mode of calculating the variance sequence value of the envelope of each moment according to the envelope of the instantaneous frequency differential sequence of each moment is as follows:
step 41, for each moment of instant frequency difference sequence g 1 (k) Doing the following stepsTo obtain a phase-shifted signal g 2 (k)；
Step 42, utilizing g 2 (k) And g is equal to 1 (k) The envelope A (k) of the instantaneous frequency difference sequence at each moment is obtained, specifically:
the envelope a (k) of the instantaneous frequency difference sequence is theoretically a constant, so that its statistical variance reflects the characteristics of the received signal, and the variance calculation formula of a (k) is as follows:
wherein the method comprises the steps of
A (k) is the envelope of the k-th sampling instant instantaneous frequency differential sequence, A (k+i) is the envelope of the k+i-th sampling instant instantaneous frequency differential sequence, i is the sum variable, D [ A (k) ]]Is the variance of a (k), M is the sliding window length,the envelope average value of all instantaneous frequency difference sequences in the window from the kth to the Mth sampling time.
The invention takes the variance sequence value D [ A (k) ] of the envelope at each moment as the detection statistic, compares the detection statistic with the threshold TH, if the detection statistic is smaller than the threshold TH, the detection result is signal, if not, the detection result is no signal. The threshold TH is determined by adopting a constant false alarm detection criterion, namely, determining the threshold according to the false alarm probability under the noise condition.
Example 2:
the sinusoidal frequency modulation signal detection device under the large Doppler condition comprises a storage device, a processor and a computer program which is stored in the storage device and can run on the processor, wherein the processor executes the computer program to realize the sinusoidal frequency modulation signal detection method under the large Doppler condition as described in the embodiment 1.
Verification test:
the simulation data is adopted to verify the sine frequency modulation signal detection method under the large Doppler condition designed by the invention, and the process result is explained.
Scene one:
the signal is sinusoidal frequency modulation signal, the center frequency f 0 =10khz, modulation index m f =5, modulation frequency f m =10, pulse width 50ms; the noise is band-pass Gaussian white noise, and the noise frequency range is 1 k-20 kHz; the sampling rate is 100kHz.
The probability density of detection statistics (i.e. variance of instantaneous frequency differential sequence envelope) under the conditions of 0dB, -5dB, -10dB and pure noise is analyzed by adopting the Monte Carlo method, and the statistics are carried out 1000 times. The specific procedure for each set of signals is as follows:
step 1: carrying out narrow-band filtering on the received echo signals, wherein a 128-order FIR band-pass filter is selected;
step 2: performing Hilbert transform on the signal subjected to the narrow-band filtering in the step 1, and estimating the instantaneous frequency of the signal;
step 3: performing differential calculation on the instantaneous frequency obtained by the calculation in the step 2 to obtain an instantaneous frequency differential sequence;
step 4: further calculating and obtaining an envelope of the instantaneous frequency differential sequence by utilizing the result of the step 3, and a variance sequence of the envelope;
the variance of the instantaneous frequency differential sequence envelope of each set of signals was calculated as described above and analyzed for probability density distribution curves under 0dB, -5dB, -10dB and pure noise conditions (see fig. 2). It can be seen that at high signal-to-noise ratios, the mean value of the variance of the instantaneous frequency differential sequence envelope is small, and the dispersion is also small; as the signal-to-noise ratio decreases, the mean value of the variance of the instantaneous frequency differential sequence envelope becomes progressively larger, and the dispersion increases, so that it is reasonable to determine the variance of the instantaneous frequency differential sequence envelope as the detection statistic.
Scene II: the signal is sinusoidal frequency modulation signal, the center frequency f 0 =10khz, modulation index m f =5, modulation frequency f m =10, pulse width 50ms; the noise is band-pass Gaussian white noise, and the noise frequency range is 1 k-20 kHz; the signal-to-noise ratio is 0dB, and the signal arrival time is 0.1s; radial velocity 20m/s; the sampling rate is 100kHz. The signal waveforms are as shown in fig. 3.
And (4) calculating according to the steps 1 to 4 to obtain detection statistics, comparing the detection statistics with a threshold to judge whether the signal exists or not (as shown in fig. 4), and obviously judging that the signal exists when the detection statistics are smaller than the threshold within the time of 0.1s to 0.2 s. Thereby verifying the effectiveness of the method of the present invention.
Scene III:
the signal is sinusoidal frequency modulation signal, the center frequency f 0 =10khz, modulation index m f =5, modulation frequency f m =10, pulse width 50ms; the noise is band-pass Gaussian white noise, and the noise frequency range is 1 k-20 kHz; the sampling rate is 100kHz.
The performance of the detection device provided by the invention is compared with that of a matched filter under different radial speeds (15 m/s, 25m/s and 35 m/s) by adopting a Monte Carlo method, and the result is shown in figure 5. As can be seen from fig. 5, the detection performance of the existing matched filter gradually decreases with the increase of doppler (i.e., the radial velocity of the target) as can be seen from the curves B2, B4 and B6, and the performance of the detection device of the present invention is not affected by doppler basically as can be seen from the curves B1, B3 and B5. When the target radial speed is 15m/s, the curves B1 and B2 can show that the performance of the method provided by the invention is improved by about 10dB compared with that of the matched filter, and the method can obtain higher detection probability under the condition of lower signal-to-noise ratio, and the detection performance is better than that of the matched filter. Therefore, the detection performance of the existing matched filter gradually decreases along with the increase of Doppler, and the performance of the detection device provided by the invention is basically not affected by Doppler, and the performance is superior to that of the matched filter.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that the different dependent claims and the features described herein may be combined in ways other than as described in the original claims. It is also to be understood that features described in connection with separate embodiments may be used in other described embodiments.
Claims (6)
1. The sine frequency modulation signal detection method under the condition of large Doppler is characterized by comprising the following steps:
step 1, carrying out narrow-band filtering on echo signals received by a receiving platform;
step 2, hilbert transformation is carried out on the signals subjected to the narrow-band filtration in the step 1, and the instantaneous frequency of each moment of the signals subjected to the narrow-band filtration is estimated;
step 3, obtaining an instantaneous frequency differential sequence of each moment by carrying out differential calculation on the instantaneous frequency of each moment;
step 4, calculating and obtaining the envelope of the instantaneous frequency differential sequence of each moment in the period of the echo signal according to the instantaneous frequency differential sequence of each moment, and calculating the variance sequence value of the envelope of each moment according to the envelope of the instantaneous frequency differential sequence of each moment;
the realization mode of calculating and obtaining the envelope of the instantaneous frequency differential sequence of each moment in the period of the echo signal according to the instantaneous frequency differential sequence of each moment is as follows:
step 41, for each moment of instant frequency difference sequence g 1 (k) Doing the following stepsTo obtain a phase-shifted signal g 2 (k) The method comprises the steps of carrying out a first treatment on the surface of the k is the serial number of the sampling time;
step 42, utilizing g 2 (k) And g is equal to 1 (k) Obtaining an envelope A (k) of the instantaneous frequency differential sequence at each moment;
the implementation mode for calculating the variance sequence value of the envelope at each moment is as follows:
calculating variance of envelope A (k) of instantaneous frequency difference sequence at each moment to obtain variance sequence value of envelope at each moment
Wherein,
a (k) is the envelope of the k-th sampling instant instantaneous frequency differential sequence, A (k+i) is the envelope of the k+i-th sampling instant instantaneous frequency differential sequence, i is the sum variable, D [ A (k) ]]Is the variance of a (k), M is the sliding window length,the envelope average value of all instantaneous frequency differential sequences in a window from the kth sampling time to the Mth sampling time;
step 5, comparing the variance sequence value of the envelope at each moment with a threshold TH as a detection statistic; and when the value is smaller than the threshold TH, determining that the sinusoidal frequency modulation signal exists in the echo signal, otherwise, determining that the sinusoidal frequency modulation signal does not exist in the echo signal.
2. The method for detecting sinusoidal frequency modulated signals under large doppler conditions according to claim 1, wherein in step 1, the narrow-band filtering of the echo signals is implemented by using FIR-type band-pass filters.
3. The method for detecting sinusoidal frequency modulated signals under a large doppler condition according to claim 1, wherein in step 2, the expression of the instantaneous frequency at each moment is:
where f (k) is the instantaneous frequency of the narrowband filtered signal at the kth sampling instant, k is the sequence number of the sampling instant, τ is the sampling interval,for the phase of the echo signal after the narrowband filtering at the kth sampling instant, +>The phase of the filtered echo signal is narrowband for the (k+1) th sample time.
4. A method for detecting sinusoidal frequency modulated signals under large Doppler conditions as defined in claim 3,
where x (k) is the narrowband filtered signal at the kth sample time,the imaginary part of the signal after the hilbert transform is x (k).
5. The method for detecting sinusoidal frequency modulated signals under a large doppler condition according to claim 1, wherein in step 3, the expression of the instantaneous frequency difference sequence at each moment is:
wherein g 1 (k) For the k-th sampling instant instantaneous frequency differential sequence, f (k) is the k-th sampling instant instantaneous frequency, f (k+1) is the k+1-th sampling instant instantaneous frequency, τ is the sampling interval, and k is the sampling instant sequence number.
6. Sinusoidal frequency modulation signal detection apparatus under large doppler conditions comprising a memory device, a processor and a computer program stored in said memory device and executable on said processor, characterized in that said processor executes said computer program to implement the sinusoidal frequency modulation signal detection method under large doppler conditions as claimed in any one of claims 1 to 5.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102064891A (en) * | 2010-11-18 | 2011-05-18 | 哈尔滨工程大学 | Anti-string leakage high-accuracy time delay estimation method |
| CN108134753A (en) * | 2016-12-01 | 2018-06-08 | 南京理工大学 | The recognition methods of broadband signal modulation system |
| CN109683142A (en) * | 2018-12-04 | 2019-04-26 | 郑州轻工业学院 | Triangular linear frequency modulation continuous signal method for parameter estimation based on differential envelope detection |
| CN111948629A (en) * | 2020-07-31 | 2020-11-17 | 哈尔滨工程大学 | High-robustness large-Doppler single-frequency pulse signal detection method |
| CN113259291A (en) * | 2021-05-26 | 2021-08-13 | 哈尔滨工程大学 | Phase compensation method realized by dynamic Doppler tracking of underwater sound continuous signals |
| CN114460527A (en) * | 2022-04-12 | 2022-05-10 | 华中科技大学 | Correlation degree continuation Hibert phase-shift electronic transformer calibrator source tracing method and system |
| CN114895248A (en) * | 2022-04-14 | 2022-08-12 | 湖南艾科诺维科技有限公司 | Sinusoidal frequency modulation signal parameter estimation method, system and medium |
| CN115508788A (en) * | 2022-09-30 | 2022-12-23 | 中国航天科工集团八五一一研究所 | Channelized detection method based on robust noise floor estimation |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100702202B1 (en) * | 2005-02-23 | 2007-04-03 | 오소트론 주식회사 | Method and Apparatus for Channel Estimation to Electro-Magnetic Wave Multi Path between Sender and Receiver by Using Chirp Signal |
-
2023
- 2023-03-22 CN CN202310284226.8A patent/CN116256738B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102064891A (en) * | 2010-11-18 | 2011-05-18 | 哈尔滨工程大学 | Anti-string leakage high-accuracy time delay estimation method |
| CN108134753A (en) * | 2016-12-01 | 2018-06-08 | 南京理工大学 | The recognition methods of broadband signal modulation system |
| CN109683142A (en) * | 2018-12-04 | 2019-04-26 | 郑州轻工业学院 | Triangular linear frequency modulation continuous signal method for parameter estimation based on differential envelope detection |
| CN111948629A (en) * | 2020-07-31 | 2020-11-17 | 哈尔滨工程大学 | High-robustness large-Doppler single-frequency pulse signal detection method |
| CN113259291A (en) * | 2021-05-26 | 2021-08-13 | 哈尔滨工程大学 | Phase compensation method realized by dynamic Doppler tracking of underwater sound continuous signals |
| CN114460527A (en) * | 2022-04-12 | 2022-05-10 | 华中科技大学 | Correlation degree continuation Hibert phase-shift electronic transformer calibrator source tracing method and system |
| CN114895248A (en) * | 2022-04-14 | 2022-08-12 | 湖南艾科诺维科技有限公司 | Sinusoidal frequency modulation signal parameter estimation method, system and medium |
| CN115508788A (en) * | 2022-09-30 | 2022-12-23 | 中国航天科工集团八五一一研究所 | Channelized detection method based on robust noise floor estimation |
Non-Patent Citations (3)
| Title |
|---|
| 回波信号瞬时参数序列分析及其应用研究;梁国龙;中国优秀博硕士学位论文全文数据库(博士)工程科技Ⅱ辑;第2007年卷(第04期);第20-45页、第60-67页 * |
| 基于希尔伯特变化的微小振动激光多普勒信号处理;武颖丽 等;中国光学;第6卷(第03期);第415-420页 * |
| 基于模糊神经网络的雷达对抗目标识别模型;许抗 等;舰船电子对抗;第32卷(第04期);第68-71页 * |
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