CN118282460A - Multi-antenna received signal processing method and device in GMSK frequency hopping communication system - Google Patents

Abstract

The invention discloses a method and a device for processing multi-antenna receiving signals in a GMSK frequency hopping communication system, wherein the method comprises the following steps: judging whether the multi-antenna receiving signals are synchronous or not; if the multi-antenna received signals are synchronous, adopting a sampling matrix inversion algorithm to perform optimal beam forming on the received signals; if the multi-antenna receiving signals are not synchronous, adopting a power inversion algorithm to carry out interference suppression and synchronization on the receiving signals; and carrying out optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm. According to the scheme, a complex antenna calibration algorithm is not needed, and the real-time self-adaptive anti-interference capability of multiple antennas can be improved.

Description

Multi-antenna received signal processing method and device in GMSK frequency hopping communication system

Technical Field

The present invention relates to the field of multi-antenna signal processing technologies, and in particular, to a method, an apparatus, a computing device, and a storage medium for processing a multi-antenna received signal in a GMSK frequency hopping communication system.

Background

The status of communication unmanned aerial vehicles and satellites in the modern communication field becomes increasingly important due to the characteristics of ultra-long transmission distance, higher communication quality and the like. Under the condition that the space electromagnetic environment is more and more complex, how to ensure the normal operation of a communication unmanned aerial vehicle and a satellite is a problem to be solved urgently.

Airspace anti-interference is an important means for resisting spatial interference in the fields of radar, communication and the like. The traditional antenna pattern is mainly determined by the shape of the antenna, the shape of the pattern cannot be designed, and the position of the pattern null can not be adjusted in a self-adaptive manner, and by adopting an airspace self-adaptive anti-interference technology, the pattern control can be conveniently carried out by multiple antennas, the null can be formed in a self-adaptive manner for the interference with unknown direction in the space, and the purpose of protecting useful signals is achieved.

The space domain self-adaptive filtering uses multiple antennas, and an adaptive beam directional diagram is formed by weighting and superposing signals received by each array element in the multiple antennas, so that a main lobe of the directional diagram is aligned to the position of a desired signal, and a null is aligned to an interference position, thereby realizing effective receiving of the desired signal, and further realizing space domain filtering on signals with different space incidence directions.

The existing spatial filtering needs to perform antenna calibration, so that a calibration antenna is needed, and a complex antenna calibration algorithm is needed, so that the implementation difficulty is high.

Disclosure of Invention

In order to solve the problems in the prior art, the scheme provides a multi-antenna receiving signal processing method, a device, a computing device and a storage medium of a GMSK frequency hopping communication system, and can improve the real-time self-adaptive anti-interference capability of the multi-antenna without a complex antenna calibration algorithm.

According to a first aspect of the present invention, there is provided a multi-antenna reception signal processing method of a GMSK frequency hopping communication system, comprising: judging whether the multi-antenna receiving signals are synchronous or not; if the multi-antenna received signals are synchronous, adopting a sampling matrix inversion algorithm to perform optimal beam forming on the received signals; if the multi-antenna receiving signals are not synchronous, adopting a power inversion algorithm to carry out interference suppression and synchronization on the receiving signals; and carrying out optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm.

Optionally, in the method for processing the multi-antenna receiving signal in the GMSK frequency hopping communication system provided by the present invention, a covariance matrix of the multi-antenna receiving signal and eigenvalues and eigenvectors of the covariance matrix are calculated; if the covariance matrices have equal eigenvalues and the eigenvectors are orthogonal, then the multi-antenna received signal synchronization is determined.

Optionally, in the method for processing a multi-antenna receiving signal in the GMSK frequency hopping communication system provided by the present invention, a receiving signal is constructed according to a characteristic sampling matrix, a transmitting signal matrix and a noise signal matrix of the multi-antenna: y=ax+n, where a is a multi-antenna feature sampling matrix, a= [ a (1), a (2),. The term, a (L) ], L is the number of antenna elements, a (L) is the feature vector of the L-th antenna received signal, X is the transmit signal matrix, x= [ X (1), X (2),. The term, X (L) ], where X (L) is the L-th signal vector, N is the noise signal matrix, n= [ N (1), N (2),. The term, N (L) ], where N (L) is the L-th noise vector;

And obtaining a weighting vector by inverting the characteristic sampling matrix of the multiple antennas, so that the weighted signal noise power is minimum: w=argmin { ||x-WoptY |2 }, wherein, i are euclidean norms, wopt is the optimal weight vector, wopt=a (-1) Y;

A weight vector is calculated based on the desired beam direction and shape and applied to the output of each antenna.

Optionally, in the method for processing a multi-antenna receiving signal in the GMSK frequency hopping communication system provided by the present invention, a pilot sequence in a receiving signal is used to perform synchronization position estimation, and the pilot sequence is extracted from the multi-antenna receiving sequence according to the estimated pilot synchronization position; generating a local pilot sequence based on the known pilot sequence and channel state information; and estimating a channel based on a minimum mean square error criterion by using the received pilot sequence and the local pilot sequence to obtain an optimal weight vector so as to combine the multi-antenna received signals based on the optimal weight vector.

Optionally, in the method for processing multiple antenna receiving signals in the GMSK frequency hopping communication system provided by the present invention, a signal received on a first array element is used as a reference signal, and a weighting vector of the first array element is set to be 1; adjusting the weight vectors of the rest array elements based on the received signals of the first array element, so that the mean square error of the reference signals and the output weights is minimized, and the array output is minimized; after the received signals are restrained, the optimal weight vector calculated by the sampling matrix inversion algorithm based on the last hop is adopted to combine the multi-antenna received signals; and extracting synchronous signals from the combined signals, and synchronizing signals received by the plurality of antennas by using the synchronous signals.

Optionally, in the method for processing multiple antenna receiving signals in the GMSK frequency hopping communication system provided by the present invention, frequency synchronization and phase synchronization are implemented by estimating a frequency deviation between a receiving signal and a synchronization signal and compensating the receiving signal; and measuring the frequency deviation between the received signal and the synchronous signal according to the frequency synchronization result, correcting the frequency deviation and outputting a local synchronous signal.

Optionally, in the method for processing multi-antenna receiving signals in the GMSK frequency hopping communication system provided by the present invention, sampling matrix inversion is performed based on the local synchronization signal and the receiving signal, an optimal weighting vector is obtained based on minimum mean square error criterion calculation, and the multi-antenna receiving signals are combined again; and carrying out frequency offset measurement correction, single carrier signal estimation and equalization processing on the recombined signals to recover and optimize the signals.

According to a second aspect of the present invention, there is provided a multi-antenna reception signal processing apparatus of a GMSK frequency hopping communication system, comprising: a judging module, a first self-adaptive anti-interference module, a second self-adaptive anti-interference module and a third self-adaptive anti-interference module,

The judging module is used for judging whether the multi-antenna receiving signals are synchronous or not; the first adaptive anti-interference module is used for carrying out optimal beam forming on the received signals by adopting a sampling matrix inversion algorithm under the condition of synchronization of the multi-antenna received signals; the second self-adaptive anti-interference module is used for carrying out interference suppression and synchronization on the received signals by adopting a power inversion algorithm under the condition that the received signals of the multiple antennas are not synchronous; and the third self-adaptive anti-interference module is used for carrying out optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm.

According to a third aspect of the present invention there is provided a computing module comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor performing a method of processing a multi-antenna received signal in a GMSK frequency-hopping communication system as in the first aspect.

According to a fourth aspect of the present invention there is provided a computer readable storage medium comprising a computer program stored with instructions executable by a processor to load and perform a method of processing a multi-antenna received signal in a GMSK frequency hopping communication system as in the first aspect.

According to the multi-antenna receiving signal processing method and device of the GMSK frequency hopping communication system, which are provided by the invention, the advantages of the PI algorithm and the SMI algorithm are fully utilized without a complex antenna calibration algorithm, the PI algorithm is only used for synchronization when the system is initially or the link is disconnected and enters again, the PI algorithm can use the optimal weight coefficient obtained by the previous jump of SMI calculation, and the operation time of the PI algorithm is saved;

The SMI algorithm is adopted to carry out real beam forming, the space diversity of the receiving array is utilized to improve the beam forming performance and precision, the beam forming parameters can be adaptively adjusted according to the channel state, and the robustness of the frequency hopping system is improved. Therefore, the scheme is suitable for a complex frequency hopping communication system and a scene with higher multi-beam forming performance requirement.

The foregoing description is only an overview of the present invention, and is intended to be implemented in accordance with the teachings of the present invention in order that the same may be more clearly understood and to make the same and other objects, features and advantages of the present invention more readily apparent.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:

FIG. 1 illustrates a block diagram of a computing device 100 according to one embodiment of the invention;

fig. 2 shows a flow diagram of a method 200 of processing a multi-antenna received signal of a GMSK frequency-hopping communication system according to one embodiment of the present invention;

FIG. 3 illustrates a block diagram of an SMI and PI algorithm implementation in accordance with one embodiment of the present invention;

Fig. 4 is a schematic diagram showing a structure of a multi-antenna reception signal processing apparatus of a GMSK frequency-hopping communication system according to one embodiment of the present invention;

FIG. 5 shows a three-dimensional interference-free amplitude beam pattern obtained using a sampling matrix inversion algorithm;

fig. 6 shows a three-dimensional interference-free amplitude beam pattern obtained using a power inversion algorithm.

Detailed Description

GMSK (Gaussian Minimum SHIFT KEYING ) has advantages of excellent spectrum utilization, power efficiency, and non-coherent demodulation, etc., and has been widely used in wireless communication systems.

In order to improve the strong interference resistance of a GMSK frequency hopping communication system, the scheme provides a multi-antenna receiving signal processing method in the GMSK frequency hopping communication system, and the method can directly use an SMI algorithm to carry out beam forming by combining a sampling matrix Inversion (Sample Matrix Inversion, SMI) algorithm and a Power Inversion ((Power Inversion, PI) algorithm if signals can be synchronized, and firstly use the Power Inversion algorithm to inhibit strong interference if the signals cannot be synchronized, and then use the SMI algorithm to carry out beam forming after synchronizing the multi-antenna signals.

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

FIG. 1 illustrates a block diagram of a computing device 100 according to one embodiment of the invention. As shown in FIG. 1, in a basic configuration 102, a computing device 100 typically includes a system memory 106 and one or more processors 104. The memory bus 108 may be used for communication between the processor 104 and the system memory 106.

Depending on the desired configuration, the processor 104 may be any type of processor, including, but not limited to: a microprocessor (μp), a microcontroller (μc), a digital information processor (DSP), or any combination thereof. The processor 104 may include one or more levels of caches, such as a first level cache 110 and a second level cache 112, a processor core 114, and registers 116. The example processor core 114 may include an Arithmetic Logic Unit (ALU), a Floating Point Unit (FPU), a digital signal processing core (DSP core), or any combination thereof. The example memory controller 118 may be used with the processor 104, or in some implementations, the memory controller 118 may be an internal part of the processor 104.

Depending on the desired configuration, system memory 106 may be any type of memory including, but not limited to: volatile memory (such as RAM), non-volatile memory (such as ROM, flash memory, etc.), or any combination thereof. Physical memory in a computing device is often referred to as volatile memory, RAM, and data in disk needs to be loaded into physical memory in order to be read by processor 104. The system memory 106 may include an operating system 120, one or more applications 122, and program data 124.

In some implementations, the application 122 may be arranged to execute instructions on an operating system by the one or more processors 104 using the program data 124. Operating system 120 may be, for example, linux, windows or the like, which includes program instructions for handling basic system services and performing hardware-dependent tasks. The application 122 includes program instructions for implementing various functions desired by the user, and the application 122 may be, for example, a browser, instant messaging software, a software development tool (e.g., integrated development environment IDE, compiler, etc.), or the like, but is not limited thereto. When an application 122 is installed into computing device 100, a driver module may be added to operating system 120.

When the computing device 100 starts up running, the processor 104 reads the program instructions of the operating system 120 from the memory 106 and executes them. Applications 122 run on top of operating system 120, utilizing interfaces provided by operating system 120 and underlying hardware to implement various user-desired functions. When a user launches the application 122, the application 122 is loaded into the memory 106, and the processor 104 reads and executes the program instructions of the application 122 from the memory 106.

Computing device 100 also includes storage device 132, storage device 132 including removable storage 136 and non-removable storage 138, both removable storage 136 and non-removable storage 138 being connected to storage interface bus 134.

Computing device 100 may also include an interface bus 140 that facilitates communication from various interface devices (e.g., output devices 142, peripheral interfaces 144, and communication devices 146) to basic configuration 102 via bus/interface controller 130. The example output device 142 includes a graphics processing unit 148 and an audio processing unit 150. They may be configured to facilitate communication with various external devices such as a display or speakers via one or more a/V ports 152. Example peripheral interfaces 144 may include a serial interface controller 154 and a parallel interface controller 156, which may be configured to facilitate communication with external devices such as input devices (e.g., keyboard, mouse, pen, voice input device, touch input device) or other peripherals (e.g., printer, scanner, etc.) via one or more I/O ports 158. An example communication device 146 may include a network controller 160, which may be arranged to facilitate communication with one or more other computing devices 162 via one or more communication ports 164 over a network communication link.

The network communication link may be one example of a communication medium. Communication media may typically be embodied by computer readable instructions, data structures, program modules, and may include any information delivery media in a modulated data signal, such as a carrier wave or other transport mechanism. A "modulated data signal" may be a signal that has one or more of its data set or changed in such a manner as to encode information in the signal. By way of non-limiting example, communication media may include wired media such as a wired network or special purpose network, and wireless media such as acoustic, radio Frequency (RF), microwave, infrared (IR) or other wireless media. The term computer readable media as used herein may include both storage media and communication media. In the computing device 100 according to the invention, the application 122 comprises instructions for performing the multi-antenna receive signal processing method 200 of the GMSK frequency-hopping communication system of the invention.

Fig. 2 shows a flow diagram of a method 200 for processing a multi-antenna received signal of a GMSK frequency-hopping communication system according to one embodiment of the present invention. As shown in fig. 2, the method 200 starts with step S210, and determines whether the multi-antenna received signals are synchronized.

In GMSK frequency hopping communication systems, where multiple antennas are used to simultaneously receive signals, the antennas are distributed in different locations to receive different signals in different directions, there may be some delay and phase difference.

In one embodiment of the present invention, a covariance matrix of a multi-antenna received signal and eigenvalues and eigenvectors of the covariance matrix may be calculated; if the covariance matrices have equal eigenvalues and the eigenvectors are orthogonal, then multi-antenna received signal synchronization can be determined.

For the array antennas, synchronization of signals is represented by the respective antenna reception signals having similar phases, and therefore, whether signals are synchronized can be judged by comparing the phase differences of the respective antenna reception signals.

It can also judge whether the multi-antenna receiving signals are synchronous or not by calculating the cross-correlation coefficient between the signals. For synchronous signals, the autocorrelation coefficients may exhibit clear peak structures, and for asynchronous signals, the autocorrelation coefficients may exhibit blurred or complex structures.

In step S220, if the multi-antenna received signals are synchronized, the received signals are optimally beamformed using a sampling matrix inversion algorithm.

Firstly, constructing a receiving signal according to a characteristic sampling matrix, a transmitting signal matrix and a noise signal matrix of multiple antennas:

Y＝AX+N

Wherein a is a multi-antenna feature sampling matrix, a= [ a (1), a (2),. The term, a (L) ], L is the number of antenna elements, a (L) is the feature vector of the L-th antenna received signal, X is the transmit signal matrix, x= [ X (1), X (2),. The term, X (L) ], wherein X (L) is the L-th signal vector, N is the noise signal matrix, n= [ N (1), N (2),. The term, N (L) ], wherein N (L) is the L-th noise vector.

And constructing a weighting vector by inverting the characteristic sampling matrix of the multiple antennas, so that the weighted signal noise power is minimum: w=argmin { ||x-WoptY |2 }, wherein, i are euclidean norms, wopt is the optimal weight vector, wopt=a (-1) Y.

A weight vector is calculated based on the desired beam direction and shape and applied to the output of each antenna.

The optimal weight vector Wopt is now analyzed, and there are three main beamforming criteria: minimum Mean Square Error (MMSE) beamformer, maximum signal-to-noise ratio (MaxSNR) beamformer, linear Constraint Minimum Variance (LCMV) beamformer.

The linear constraint least squares algorithm (LCMV) requires knowledge of the steering vector, i.e., the desired signal reach angle and the antenna placement position and antenna array geometry, while the Minimum Mean Square Error (MMSE) based SMI algorithm is employed, although there is still a matrix inversion, but does not require knowledge of the steering vector. The algorithm is as follows:

Where X is the original transmitted signal, i.e., the known pilot sequence, Y is the received multi-antenna signal, i.e., y=ax+n, is the covariance matrix of the received signal, Indicating that the error of the received signal Y weighted by Wopt and the local e (n) is minimal.

Since a local training sequence is required, synchronization information needs to be acquired. Specifically, the pilot sequence in the received signal may be used for synchronization position estimation, and the pilot sequence may be extracted from the multi-antenna received sequence according to the estimated pilot synchronization position.

Local pilot sequences are generated based on the known pilot sequences and channel state information. And estimating a channel based on a minimum mean square error criterion by using the received pilot sequence and the local pilot sequence to obtain an optimal weight vector so as to combine the multi-antenna received signals based on the optimal weight vector.

In step S230, if the multi-antenna received signals are not synchronized, the received signals are suppressed and synchronized using a power inversion algorithm.

The power inversion algorithm directly takes the output of the array as an error signal, and the minimum output of the array is realized by minimizing the mean square error.

Specifically, the signals received by the multiple antennas are expressed as: the number of antenna elements. The multiple antennas are weighted, and the final output of the multiple antennas can be expressed as follows.

For the power inversion algorithm, the following is calculated:

in the above expression, the value obtained by minimizing the following expression is expressed, and M represents the number of sampling points.

Taking a signal x ₀ received on the first array element as a reference signal, and setting a weight vector w ₀ of the first array element to be 1; and adjusting the weight vectors (w ₁、w₂……w_L-1) of the rest array elements based on the received signals of the first array element, so that the mean square error between the reference signals and the output weights is minimized, thereby minimizing the output of the array and realizing the suppression of the received signals.

After the received signals are suppressed, the optimal weight vector Wopt calculated by the sampling matrix inversion algorithm based on the previous hop can be adopted to combine the multi-antenna received signals.

Therefore, the operation time of the power inversion algorithm can be saved, and the pilot frequency position of the next hop and the pilot frequency position of the last hop only differ by one hop, so that the SMI algorithm can be directly used for carrying out interference beam sinking processing.

And extracting synchronous signals from the combined signals, and synchronizing signals received by the plurality of antennas by using the synchronous signals.

Specifically, firstly, frequency synchronization and phase synchronization are realized by estimating the frequency deviation between a received signal and a synchronization signal and compensating the received signal; then, the frequency deviation between the received signal and the synchronization signal is measured according to the result of the frequency synchronization, and the frequency deviation is corrected to output a local synchronization signal.

After the signal synchronization processing, the multi-antenna receiving signals can be effectively integrated, so that the system performance (such as communication capacity, transmission rate and signal strength) and coverage area are improved, and multipath effects are suppressed.

And finally, executing step S240, and performing optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm.

And carrying out sampling matrix inversion based on the local synchronous signal and the received signal, calculating to obtain an optimal weighting vector based on a minimum mean square error criterion, and merging the received signals of multiple antennas again. And carrying out frequency offset measurement correction, single carrier signal estimation and equalization processing on the recombined signals to recover and optimize the signals.

The frequency offset is caused by inaccuracy of the local oscillation frequency of the transmitting and receiving apparatuses, and an autocorrelation function method may be used to estimate a frequency offset value for correction of the frequency offset and use it as a reference for frequency compensation.

After the received signal is subjected to frequency offset correction, channel fading and noise may still exist, and a minimum mean square error equalization technology may be used to restore the original single carrier signal by comparing and matching the received signal with a known reference sequence.

After single carrier signal estimation, there may be problems of channel time variability, multipath effect, etc., in order to counteract these interferences, an adaptive equalization processing method may be adopted, and by adjusting the amplitude and phase of each moment in the received signal, recovery and optimization of the signal may be realized.

FIG. 3 illustrates a block diagram of an SMI and PI algorithm implementation in accordance with one embodiment of the present invention. As shown in fig. 3, for ka-root antennas, the covariance matrix is first solved, a power inversion algorithm is performed to obtain a combined signal, signal synchronization and frequency offset measurement correction are performed, meanwhile, the local sequence and the receiving sequence are notified to perform an SMI sampling matrix inversion algorithm, an optimal weight coefficient is calculated based on a minimum mean square error criterion, the ka-root antennas are combined into a channel again based on the optimal weight coefficient, frequency offset correction and synchronization correction are performed again, and single-carrier single-channel signal estimation and equalization processing are performed.

It should be noted that the processing of the power inversion algorithm is only used at the beginning of the system or when the system is re-entered after the link is disconnected. The optimal weight coefficient obtained by calculation of the SMI algorithm of the previous jump can be adopted for each multi-antenna combination, so that the processing time of the PI algorithm can be saved. The pilot frequency position of the next hop and the pilot frequency position of the last hop are only different in time, so that the SMI algorithm can be directly used for carrying out interference beam sinking processing, and the simplified algorithm has great practicability for a frequency hopping communication system.

Fig. 4 shows a schematic diagram of a multi-antenna received signal processing apparatus of a GMSK frequency hopping communication system according to one embodiment of the present invention. As shown in fig. 4, the apparatus 400 may include: the device comprises a judging module 410, a first adaptive anti-interference module 420, a second adaptive anti-interference module 430 and a third adaptive anti-interference module 440.

The determining module 410 may determine whether the multiple antenna receiving signals are synchronized. In a frequency hopping system, synchronization of multiple antenna reception signals may be interfered to some extent due to the influence of channel conditions, multipath propagation, and the like. Therefore, in judging synchronization, various factors such as time, frequency, chips and the like need to be comprehensively considered, and proper algorithms and techniques are adopted to perform synchronization detection and correction.

The first adaptive anti-interference module 420 may perform optimal beamforming on the received signal using a sampling matrix inversion algorithm under the condition that the multiple antenna received signals are synchronized. The second adaptive anti-interference module 430 may perform interference suppression and synchronization on the received signal using a power inversion algorithm in the case that the multi-antenna received signal is not synchronized. The third adaptive anti-interference module 440 may perform optimal beamforming on the synchronized received signal using a sampling matrix inversion algorithm.

The anti-interference effect of the sampling matrix inversion algorithm and the power inversion algorithm can be compared through simulation. The simulated input data is shown in the following table:

fig. 5 shows a three-dimensional interference-free amplitude beam pattern obtained using a sampling matrix inversion algorithm. Fig. 6 shows a three-dimensional interference-free amplitude beam pattern obtained using a power inversion algorithm. Referring to fig. 5 and 6, the beamforming pattern of the SMI algorithm has a greater interference resistance than the beamforming pattern of the PI algorithm. As shown in fig. 5, the beamforming pattern of the SMI algorithm interferes with the greater signal recess, and the suppression of the interfering signal by the SMI is (-75.67 dB, -70.14 dB). As shown in fig. 6, the PI algorithm suppresses the interference signal by (-61.18 dB, -45.56 dB). Therefore, the scheme is only used synchronously initially through the PI algorithm, and the SMI algorithm is adopted to carry out real beam forming later.

According to the method and the device for processing the multi-antenna receiving signals of the GMSK frequency hopping communication system, provided by the invention, the advantages of the PI algorithm and the SMI algorithm are fully utilized without a complex antenna calibration algorithm, the PI algorithm is used for synchronization only when the system is initially or the link is disconnected and enters again, the PI algorithm can use the optimal weight coefficient obtained by the previous hop of SMI calculation, and the operation time of the PI algorithm is saved;

The SMI algorithm is adopted to carry out real beam forming, the space diversity of the receiving array is utilized to improve the beam forming performance and precision, the beam forming parameters can be adaptively adjusted according to the channel state, and the robustness of the frequency hopping system is improved. Therefore, the scheme is suitable for a complex frequency hopping communication system and a scene with higher multi-beam forming performance requirement.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

As used herein, unless otherwise specified the use of the ordinal terms "first," "second," "third," etc., to describe a general object merely denote different instances of like objects, and are not intended to imply that the objects so described must have a given order, either temporally, spatially, in ranking, or in any other manner.

Claims (10)

1. A multi-antenna received signal processing method of a GMSK frequency hopping communication system, comprising:

judging whether the multi-antenna receiving signals are synchronous or not;

If the multi-antenna received signals are synchronous, adopting a sampling matrix inversion algorithm to perform optimal beam forming on the received signals;

if the multi-antenna receiving signals are not synchronous, adopting a power inversion algorithm to carry out interference suppression and synchronization on the receiving signals;

And carrying out optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm.

2. The method for processing a multi-antenna received signal in a GMSK frequency-hopping communication system of claim 1, wherein the step of determining whether the multi-antenna received signals are synchronized comprises:

calculating a covariance matrix of the multi-antenna received signals and eigenvalues and eigenvectors of the covariance matrix;

if the covariance matrices have equal eigenvalues and the eigenvectors are orthogonal, then the multi-antenna received signal synchronization is determined.

3. The method for processing a multi-antenna received signal in a GMSK frequency-hopping communication system of claim 1, wherein the step of optimally beamforming the received signal using a sampling matrix inversion algorithm if the multi-antenna received signal is synchronized comprises:

constructing a receiving signal according to the characteristic sampling matrix, the transmitting signal matrix and the noise signal matrix of the multiple antennas: y=ax+n, where a is a multi-antenna feature sampling matrix, a= [ a (1), a (2),. The term, a (L) ], L is the number of antenna elements, a (L) is the feature vector of the L-th antenna received signal, X is the transmit signal matrix, x= [ X (1), X (2),. The term, X (L) ], where X (L) is the L-th signal vector, N is the noise signal matrix, n= [ N (1), N (2),. The term, N (L) ], where N (L) is the L-th noise vector;

And inverting the characteristic sampling matrix of the multiple antennas to construct a weighting vector, so that the weighted signal noise power is minimum: w=argmin { ||x-WoptY |2 }, wherein, i are euclidean norms, wopt is the optimal weight vector, wopt=a (-1) Y;

A weight vector is calculated based on the desired beam direction and shape and applied to the output of each antenna.

4. A method of processing a multi-antenna received signal in a GMSK frequency-hopping communication system according to claim 3, wherein the step of calculating a weight vector according to a desired beam direction and shape and applying the weight vector to an output of each antenna comprises:

Using pilot frequency sequence in the received signal to estimate the synchronous position, extracting pilot frequency sequence in the multi-antenna receiving sequence according to the estimated pilot frequency synchronous position;

generating a local pilot sequence based on the known pilot sequence and channel state information;

and estimating a channel based on a minimum mean square error criterion by using the received pilot sequence and the local pilot sequence to obtain an optimal weight vector so as to combine the multi-antenna received signals based on the optimal weight vector.

5. The method for processing a multi-antenna received signal in a GMSK frequency-hopping communication system of claim 1, wherein the step of performing interference suppression and synchronization on the received signal using a power inversion algorithm if the multi-antenna received signal is not synchronized comprises:

taking the signal received on the first array element as a reference signal, and setting the weighting vector of the first array element as 1;

Adjusting the weight vectors of the rest array elements based on the received signals of the first array element, so that the mean square error of the reference signals and the output weights is minimized, and the array output is minimized;

after the received signals are restrained, the optimal weight vector calculated by the sampling matrix inversion algorithm based on the last hop is adopted to combine the multi-antenna received signals;

And extracting synchronous signals from the combined signals, and synchronizing signals received by the plurality of antennas by using the synchronous signals.

6. The method for processing multi-antenna received signals in a GMSK frequency-hopping communication system of claim 5 wherein the step of extracting the synchronization signals from the combined signals and using the synchronization signals to synchronize the signals received by the plurality of antennas, respectively, comprises:

frequency synchronization and phase synchronization are realized by estimating the frequency deviation between the received signal and the synchronization signal and compensating the received signal;

and measuring the frequency deviation between the received signal and the synchronous signal according to the frequency synchronization result, correcting the frequency deviation and outputting a local synchronous signal.

7. The method for processing multiple antenna received signals in a GMSK frequency-hopping communication system of claim 6 wherein the step of performing optimal beamforming on the synchronized received signals using a sampling matrix inversion algorithm comprises:

sampling matrix inversion is carried out based on the local synchronous signals and the received signals, an optimal weighting vector is obtained based on minimum mean square error criterion calculation, and the received signals of multiple antennas are combined again;

and carrying out frequency offset measurement correction, single carrier signal estimation and equalization processing on the recombined signals to recover and optimize the signals.

8. A multi-antenna reception signal processing apparatus of a GMSK frequency hopping communication system, comprising: a judging module, a first self-adaptive anti-interference module, a second self-adaptive anti-interference module and a third self-adaptive anti-interference module,

The judging module is used for judging whether the multi-antenna receiving signals are synchronous or not;

the first adaptive anti-interference module is used for performing optimal beam forming on the received signals by adopting a sampling matrix inversion algorithm under the condition of synchronization of the multi-antenna received signals;

The second adaptive anti-interference module is used for carrying out interference suppression and synchronization on the received signals by adopting a power inversion algorithm under the condition that the received signals of the multiple antennas are not synchronous;

And the third self-adaptive anti-interference module is used for carrying out optimal beam forming on the synchronized received signals by adopting a sampling matrix inversion algorithm.

9. A computing device, comprising:

At least one processor; and

A memory storing program instructions, wherein the program instructions are configured to be adapted to be executed by the at least one processor, the program instructions comprising instructions for performing the method of multi-antenna receive signal processing in a GMSK frequency-hopping communication system of any one of claims 1-7.

10. A readable storage medium storing program instructions which, when read and executed by a computing device, cause the computing device to perform the method of multi-antenna receive signal processing in a GMSK frequency-hopping communication system of any one of claims 1-7.