Adaptive interference suppression method and system based on spectrum analysis

Abstract

This invention discloses an adaptive interference suppression method and system based on spectrum analysis, belonging to the field of radar signal interference suppression technology. The method includes: acquiring multiple digital intermediate frequency (IF) interference signals; performing spectrum analysis on each IF interference signal to obtain signal spectrum analysis results; adjusting the sub-band filter structure based on the signal spectrum analysis results to ensure that the number of interference signals within any sub-band satisfies interference suppression; inputting each IF interference signal into the adjusted sub-band filter to obtain corresponding multi-channel sub-band signals; inputting each sub-band signal into an adaptive interference suppression structure, and using the signal spectrum analysis results for the initial calculation of the optimal weight vector to obtain a synthesized signal. This invention performs spectrum analysis on the interference signal and adaptively modifies the parameters of various interference suppression parameters based on the spectrum analysis results, thereby achieving optimal interference suppression effect with fixed hardware resource consumption.

Description

Technical Field

[0001] This invention belongs to the field of interference suppression technology for measurement and control communication signals, specifically relating to an adaptive interference suppression method and system based on spectrum analysis. Background Technology

[0002] For common interference suppression techniques in array signal processing, when the number of antenna elements in the array antenna is limited and signal processing resources are also limited, the number of interference sources that can be suppressed is limited by the number of array elements without special processing. Furthermore, with a fixed amount of processing resources, the interference suppression effect usually weakens as the processing bandwidth increases. Figure 1 The matched filtering results for a uniform linear array (with 4 elements) in the absence of interference are presented. Figure 2 , Figure 3 , Figure 4 The images show the matched filtering results of the output signal and the desired signal after interference suppression in four-element arrays under single-interference, three-interference, and four-interference environments, respectively. It can be seen that as the number of interferences increases, the interference suppression effect gradually weakens until it fails (the signal-to-noise ratio decreases after matched filtering). Furthermore, in the aforementioned multi-interference environments, the bandwidth, intensity (interference-to-noise ratio), center frequency, and angle of the interference signals are not entirely the same. Therefore, when the number of interferences is large and the interference bandwidth and center frequency of the interference signals are inconsistent, it is necessary to modify the interference suppression structure to achieve the optimal interference suppression effect.

[0003] like Figure 5 As shown, a conventional interference suppression system structure includes a receiving array antenna, an RF front-end (down-conversion structure), an analog-to-digital conversion circuit, and an interference suppression signal processing module that divides (or does not divide) sub-bands. The suppressed signal is then output for further processing. Typically, in interference suppression, the number of interferences in each sub-band needs to be less than the number of receiving antenna elements minus one.

[0004] In environments where the number of interferences, interference bandwidth, and interference center frequency are unknown, commonly used methods include: (1) interference suppression in the space-frequency domain; and (2) interference suppression in the space-time (space-frequency) domain with fixed sub-band division. Both methods share a common drawback: they do not analyze the received signal spectrum and instead employ fixed sub-band or multi-frequency adaptive filtering techniques, making the interference suppression effect highly dependent on the distribution of the interference signal. For example, in a system with a desired signal bandwidth of 20MHz, if there are 10 interferences and their distribution is as follows... Figure 6As shown, subband 1 has 1 interference signal, subband 2 has 3 interference signals, subbands 3 and 5 have no interference, while subband 4 has 6 interference signals. The interference signal bandwidth is discretely distributed across each subband. Assuming the array has 4 elements, we can see that subbands 3 and 5 do not require interference suppression (in practice, computational resources are consumed due to the unknown presence of interference). Subband 1 has the best interference suppression effect (relative to the interfering subbands), while subband 4 fails to suppress interference. Therefore, the suppression of interference signals across the entire bandwidth fails, thus affecting the reception of the useful signal.

[0005] In related technologies, Chinese invention patent application CN103116170A discloses an indoor testing system for GNSS based on an antenna array interference suppression module. This system utilizes a multi-channel digital intermediate frequency (IF) interference signal generation unit to generate multiple IF digital IF interference signals. The interference suppression processing unit is a GNSS-based antenna array interference suppression module used to suppress the multiple IF digital IF interference signals generated by the multi-channel digital IF interference signal generation unit, and the signal after interference suppression is analyzed using a spatial spectrum method. However, this scheme analyzes the signal after interference suppression using a spatial spectrum method, without analyzing the received signal spectrum, resulting in a failure in interference suppression. Summary of the Invention

[0006] The technical problem to be solved by this invention is how to improve the effect of interference suppression while consuming fixed hardware resources.

[0007] The present invention solves the above-mentioned technical problems through the following technical means:

[0008] This invention proposes an adaptive interference suppression method based on spectrum analysis, the method comprising the following steps:

[0009] Acquire multiple digital intermediate frequency interference signals;

[0010] Spectral analysis is performed on each of the digital intermediate frequency interference signals to obtain signal spectrum analysis results, which include the angle, bandwidth, amplitude, and number of interference signals.

[0011] Based on the signal spectrum analysis results, the subband filter structure is adjusted so that the number of interferences in any subband meets the interference suppression requirement.

[0012] Each of the digital intermediate frequency interference signals is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0013] Each sub-band signal is input into an adaptive interference suppression structure, and the signal spectrum analysis results are used for the initial calculation of the optimal weight vector to obtain the synthesized signal.

[0014] Before suppressing digital intermediate frequency (IF) interference signals, this invention first performs spectral analysis on the IF interference signals to obtain spectral analysis results. Based on the spectral analysis results, it adaptively modifies various interference suppression parameters, thereby achieving the optimal interference suppression effect with a fixed hardware resource consumption.

[0015] Furthermore, the step of performing spectral analysis on each of the digital intermediate frequency interference signals to obtain the signal spectral analysis results includes:

[0016] Perform a fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time-domain signals to the frequency domain, and obtain the corresponding multi-channel sub-band signals.

[0017] Perform a modulus-square operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal.

[0018] Based on the power spectrum, a threshold is used to determine whether there is an interference signal in each of the sub-band signals.

[0019] All sub-band signals with interfering signals are divided into frequency bandwidths to the minimum bandwidth.

[0020] Signal processing is performed on all sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

[0021] Furthermore, adjusting the subband filter structure based on the signal spectrum analysis results includes:

[0022] Based on the minimum bandwidth of the second subband signal and the number of interferences within the subband, the order of the subband filter is set to be greater than the number of interferences within the subband.

[0023] Based on the minimum bandwidth of the second subband signal, the tap interval of the subband filter is set, where the tap interval D = fs / B, and fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

[0024] Further, the step of inputting each of the digital intermediate frequency interference signals into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal includes:

[0025] The digital intermediate frequency interference signals from each channel are converted from time-domain signals to frequency-domain signals by fast Fourier transform.

[0026] Each of the digital intermediate frequency interference signals in the frequency domain is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0027] Furthermore, the method also includes:

[0028] The synthesized signal is subjected to inverse fast Fourier transform to convert the frequency domain signal to the time domain for back-end processing.

[0029] Furthermore, this invention also proposes an adaptive interference suppression system based on spectrum analysis, the system comprising:

[0030] Interference signal generation module, used to generate multiple digital intermediate frequency interference signals;

[0031] The spectrum analysis module is used to perform spectrum analysis on each of the digital intermediate frequency interference signals to obtain the signal spectrum analysis results, which include the angle, bandwidth, amplitude and number of interference signals.

[0032] The filter adjustment module is used to adjust the sub-band filter structure based on the signal spectrum analysis results. Each of the digital intermediate frequency interference signals is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0033] An adaptive interference suppression module is used to use the signal spectrum analysis results for the initial calculation of the optimal weight vector, and to synthesize each of the sub-band signals to obtain a synthesized signal.

[0034] Furthermore, the interference signal generation module includes a receiving array antenna, a radio frequency front-end, and an analog-to-digital conversion circuit;

[0035] The output of the receiving array antenna is connected to the radio frequency front end, and the output of the radio frequency front end is connected to the analog-to-digital conversion circuit;

[0036] The output of the analog-to-digital conversion circuit is connected to the spectrum analysis module and the adaptive interference suppression structure, respectively.

[0037] Furthermore, the spectrum analysis module includes a first FFT module, a modulus-squared module, a sub-band division module, a threshold determination module, and a signal angle prediction module, wherein:

[0038] The first FFT module is used to perform fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time domain signal to the frequency domain and obtain the corresponding multi-subband signal.

[0039] The modulus squaring module is used to perform a modulus squaring operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal.

[0040] The sub-band division module is used to determine whether there is an interference signal in each sub-band signal 2 based on the power spectrum and the threshold determination module, and to divide the frequency bandwidth of all sub-band signals 2 with interference signals to the minimum bandwidth.

[0041] The signal angle prediction module is used to perform signal processing on all sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

[0042] Furthermore, the filter adjustment module includes:

[0043] The order setting unit is used to set the order of the subband filter to be greater than the number of interferences in the subband, based on the minimum bandwidth of the second subband signal and the number of interferences in the subband.

[0044] The tap interval setting unit is used to set the tap interval of the subband filter according to the minimum bandwidth of the second subband signal, wherein the tap interval D = fs / B, where fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

[0045] Based on the signal spectrum analysis results, the parameters of the subband filter are adjusted so that the number of interferences in any subband meets the interference suppression requirement.

[0046] Furthermore, the system also includes an IFFT module, which performs an inverse fast Fourier transform on the synthesized signal to convert the frequency domain signal to the time domain for back-end processing.

[0047] The advantages of this invention are:

[0048] (1) Before suppressing the digital intermediate frequency interference signal, the present invention first performs spectrum analysis on the digital intermediate frequency interference signal to obtain the spectrum analysis results, and based on the spectrum analysis results, adaptively modifies the parameters of each interference suppression, thereby achieving the optimal interference suppression effect with a fixed consumption of hardware resources.

[0049] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of the matched filtering result of the uniform linear array (with 4 array elements) mentioned in the background section of this invention when there is no interference.

[0051] Figure 2 This is a schematic diagram of the matched filtering result of the output signal and the desired signal after the 4-element array is subjected to interference suppression in a single interference environment, as mentioned in the background section of this invention.

[0052] Figure 3 This is a schematic diagram of the matched filtering result of the output signal and the desired signal after the 4-element array is subjected to interference suppression in a three-interference environment, as mentioned in the background section of this invention.

[0053] Figure 4This is a schematic diagram of the matched filtering result of the output signal and the desired signal after the four array elements are subjected to interference suppression in a four-interference environment, as mentioned in the background section of this invention.

[0054] Figure 5 This is a structural diagram of a conventional interference suppression system mentioned in the background section of this invention;

[0055] Figure 6 This is a schematic diagram of the fixed sub-band mentioned in the background section of this invention;

[0056] Figure 7 This is a flowchart illustrating the adaptive interference suppression method based on spectrum analysis proposed in the first embodiment of the present invention.

[0057] Figure 8 This is a flowchart illustrating the spectrum analysis of digital intermediate frequency interference signals in the first embodiment of the present invention;

[0058] Figure 9 This is a schematic diagram of subband division after spectral analysis in the first embodiment of the present invention;

[0059] Figure 10 This is a structural diagram of the adaptive interference suppression system based on spectrum analysis proposed in the second embodiment of the present invention;

[0060] Figure 11 This is a structural diagram of the spectrum analysis module in the second embodiment of the present invention;

[0061] Figure 12 This is a schematic diagram of the adaptive interference suppression module in the second embodiment of the present invention;

[0062] Figure 13 This is the spectrum diagram of the 4-element, 6-interference received signal in this invention;

[0063] Figure 14 This is a schematic diagram of the matched filtering result after using the method of the present invention to suppress interference in a 4-element 6-interference signal. Detailed Implementation

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] like Figure 7 As shown, the first embodiment of the present invention proposes an adaptive interference suppression method based on spectrum analysis, the method comprising the following steps:

[0066] S10: Acquire multiple digital intermediate frequency interference signals.

[0067] It should be noted that in this embodiment, the generation of multiple digital intermediate frequency interference signals can be achieved through an interference signal generation module. The interference signal generation module may include a receiving array antenna, a radio frequency front-end (down-conversion structure), and an analog-to-digital conversion circuit. The number of radio frequency front-ends and analog-to-digital conversion circuits is the same as the number of antennas in the array antenna. The output terminal of the receiving array antenna is connected to the radio frequency front-end, and the output terminal of the radio frequency front-end is connected to the analog-to-digital conversion circuit. The multiple analog-to-digital conversion circuit outputs multiple digital intermediate frequency interference signals.

[0068] S20. Perform spectrum analysis on each of the digital intermediate frequency interference signals to obtain the signal spectrum analysis results, which include the angle, bandwidth, amplitude and number of interference signals.

[0069] S30. Based on the signal spectrum analysis results, adjust the sub-band filter structure so that the number of interferences in any sub-band meets the interference suppression requirement.

[0070] It should be noted that, unlike the traditional method of using fixed filters to divide subbands for interference suppression, this embodiment adaptively adjusts the results of the subband filters based on signal spectrum analysis to ensure that the number of interferences in any subband meets the conditions for interference suppression.

[0071] S40. Input each of the digital intermediate frequency interference signals into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0072] S50. Input each of the sub-band signals into the adaptive interference suppression structure, and use the signal spectrum analysis results for the initial calculation of the optimal weight vector to obtain the synthesized signal.

[0073] This embodiment performs spectral analysis on the digital intermediate frequency (IF) interference signal before suppressing it, obtains the spectral analysis results, and adaptively adjusts the structure of the subband filter based on the spectral analysis results, as well as adaptively modifies various interference suppression parameters, thereby achieving the optimal interference suppression effect with a fixed hardware resource consumption.

[0074] In one embodiment, such as Figure 8 As shown, step S20 includes the following steps:

[0075] S21. Perform a fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time-domain signal to the frequency domain and obtain the corresponding multi-channel sub-band signal.

[0076] S22. Perform a modulus-square operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal.

[0077] S23. Based on the power spectrum, a threshold is used to determine whether there is an interference signal in each of the sub-band signals.

[0078] S24. Divide the frequency bandwidth of all the sub-band signals with interference signals to the minimum bandwidth;

[0079] S25. Perform signal processing on all sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

[0080] It should be noted that this embodiment uses array signal processing technology to estimate the number of signal sources and the signal angle of all sub-band signals with interference signals; and performs statistical analysis on the estimated signal angle, signal bandwidth, and signal amplitude characteristics to obtain information such as the angle, bandwidth, and number of interference signals as the spectrum analysis results.

[0081] In one embodiment, step S30 includes the following steps:

[0082] Based on the minimum bandwidth of the second subband signal and the number of interferences within the subband, the order of the subband filter is set to be greater than the number of interferences within the subband.

[0083] Based on the minimum bandwidth of the second subband signal, the tap interval of the subband filter is set, where the tap interval D = fs / B, and fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

[0084] Based on the spectrum analysis results, this embodiment modifies the number of sub-bands, the number of time-domain taps for interference suppression, and the tap interval. According to the number and width of the interference signals, the number of sub-bands is first divided, and then the number of taps is set according to the number of interferences in each sub-band. The tap interval is set according to the sub-band bandwidth.

[0085] By adaptively modifying the parameters of various interference suppression based on the spectrum analysis results, the optimal interference suppression effect can be achieved with a fixed hardware resource consumption.

[0086] In one embodiment, step S40 includes the following steps:

[0087] S41. The digital intermediate frequency interference signals of each channel are converted from time domain signals to frequency domain signals by fast Fourier transform.

[0088] S42. Input each of the digital intermediate frequency interference signals in the frequency domain into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0089] It should be noted that, in practical applications, the Fast Fourier Transform (FFT) for spectral analysis of digital intermediate frequency (IF) interference signals and the FFT for inputting the digital IF interference signals into the subband filter can be implemented using the same FFT module.

[0090] Furthermore, this embodiment adaptively adjusts the subband filter structure based on the results of signal spectrum analysis to achieve the condition that the number of interferences in any subband meets the interference suppression requirement. Figure 9 The results of subband division after spectral analysis are given, and... Figure 6 In comparison, the number of sub-bands remains the same, meaning the required hardware resources remain the same, but it is clearly visible that... Figure 9 The partitioning satisfies the requirement that the number of interference elements is less than the number of array elements.

[0091] In one embodiment, the method further includes:

[0092] The synthesized signal is subjected to inverse fast Fourier transform to convert the frequency domain signal to the time domain for back-end processing.

[0093] It should be understood that this embodiment can also directly use frequency domain signals for back-end processing.

[0094] In one embodiment, the adaptive interference suppression structure runs an interference suppression algorithm, specifically the LMS algorithm with space-time adaptive processing, and the processing steps are as follows:

[0095] (1) Initialization

[0096]

[0097]

[0098] The input vector is: u(0) = [u(0) 0 … 0] T

[0099] (2) For n = 0, 1, 2, ..., update the weight vector:

[0100]

[0101] Estimation of the desired signal:

[0102]

[0103] Error estimation:

[0104]

[0105] (3) Let n = n + 1 and go to step (2).

[0106] In addition, such as Figures 10 to 12As shown, the second embodiment of the present invention also proposes an adaptive interference suppression system based on spectrum analysis, the system comprising:

[0107] Interference signal generation module 10 is used to generate multiple digital intermediate frequency interference signals;

[0108] The spectrum analysis module 20 is used to perform spectrum analysis on each of the digital intermediate frequency interference signals to obtain the signal spectrum analysis results, which include the angle, bandwidth, amplitude and number of interference signals.

[0109] The filter adjustment module 30 is used to adjust the sub-band filter structure based on the signal spectrum analysis results. Each of the digital intermediate frequency interference signals is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

[0110] The adaptive interference suppression module 40 is used to use the signal spectrum analysis results for the initial calculation of the optimal weight vector, and to synthesize each of the sub-band signals to obtain a synthesized signal.

[0111] It should be noted that the output of the interference signal generation module 10 is connected to the spectrum analysis module 20 and the adaptive interference suppression module 40 respectively. The spectrum analysis module 20 is connected to the adaptive interference suppression module 40 via the filter adjustment module 30.

[0112] In one embodiment, the interference signal generation module 10 includes a receiving array antenna, a radio frequency front end, and an analog-to-digital conversion circuit;

[0113] The output of the receiving array antenna is connected to the radio frequency front end, and the output of the radio frequency front end is connected to the analog-to-digital conversion circuit;

[0114] The output of the analog-to-digital conversion circuit is connected to the spectrum analysis module and the adaptive interference suppression structure, respectively.

[0115] In one embodiment, such as Figure 11 As shown, the spectrum analysis module 20 includes a first FFT module 21, a modulus square module 22, a sub-band division module 23, a threshold determination module 24, and a signal angle prediction module 25, wherein:

[0116] The first FFT module 21 is used to perform fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time domain signal to the frequency domain and obtain the corresponding multi-channel sub-band signal 2.

[0117] Modulus squaring module 22 is used to perform a modulus squaring operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal.

[0118] Subband division module 23 is used to determine whether there is an interference signal in each subband signal 2 based on the power spectrum and using the threshold determination module 24, and to divide the frequency bandwidth of all subband signals 2 with interference signals to the minimum bandwidth.

[0119] The signal angle estimation module 25 is used to perform signal processing on all the sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

[0120] In one embodiment, the filter adjustment module 30 includes:

[0121] The order setting unit is used to set the order of the subband filter to be greater than the number of interferences in the subband, based on the minimum bandwidth of the second subband signal and the number of interferences in the subband.

[0122] The tap interval setting unit is used to set the tap interval of the subband filter according to the minimum bandwidth of the second subband signal, wherein the tap interval D = fs / B, where fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

[0123] Based on the signal spectrum analysis results, this embodiment adjusts the parameters of the subband filter to ensure that the number of interferences in any subband meets the interference suppression requirement.

[0124] like Figure 12 As shown, after the subband filter structure is adjusted, the digital intermediate frequency interference signals from each channel are subjected to Fast Fourier Transform (FFT) by the second FFT module and then fed into the subband filter. The second FFT module and the first FFT module can be the same FFT module. In the adaptive interference suppression module, the results of spectral analysis are used for the initial calculation of the optimal weight vector to increase the convergence speed. After interference suppression by the variable subband filter, the subband signals are synthesized. The synthesized signal...

[0125] In one embodiment, the system further includes an IFFT module for performing an inverse fast Fourier transform on the synthesized signal to convert the frequency domain signal to the time domain for back-end processing.

[0126] It should be noted that for interference suppression using fixed filters to divide subbands without spectral analysis, due to the unknown and complex interference environment, there may be multiple interferences within one subband while some subbands are interference-free. According to the spatial adaptive filtering structure, to suppress interference signals, the weight vector W needs to be adaptively adjusted so that the array signal X = [x1, x2, ..., x...]. M ] T The signal obtained after adaptive weighting is minimized in the direction of interference, i.e., it satisfies...

[0127] W HX j ≈0, j = 0, 1, ..., K (1)

[0128] where K is the number of interferences, and X j is the received signal vector corresponding to the j-th interference direction, and its dimension is the number M of receiving array elements.

[0129] It can be seen that to make equation (1) hold, the number of array elements needs to be no less than the number of interferences, that is, K ≤ M. Usually, constraints on the signal direction are also added

[0130] W H X s = 1 (2)

[0131] where X s is the signal vector received in the desired signal direction.

[0132] Therefore, to satisfy equations (1) and (2) simultaneously, the number of interferences needs to be less than the number of array elements, that is, K < M. So, when the number of interferences in any sub-band is greater than the number of array elements, the interference suppression fails. Therefore, for the adaptive interference suppression structure of a fixed sub-band and with fixed hardware resources, there is a problem of mismatch between resources and interference suppression, resulting in the failure of interference suppression.

[0133] Before suppressing the digital intermediate frequency interference signal in this embodiment, the digital intermediate frequency interference signal is first subjected to spectrum analysis to obtain the spectrum analysis result, and the structure of the sub-band filter is adaptively adjusted based on the spectrum analysis result, and the parameters of various interference suppressions are adaptively modified, so as to achieve the optimal interference suppression effect under the condition of fixed consumption of hardware resources.

[0134] After Figure 13 performing interference suppression on the received signal spectrum of a certain channel of the 4-element array shown, with 6 interferences and an uncertain interference bandwidth, using the interference structure of the present invention, the matched filtering result is as Figure 14 shown, and it can be seen that multiple interference signals are well suppressed.

[0135] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0136] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0137] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0138] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0139] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. An adaptive interference suppression method based on spectrum analysis, characterized in that, The method includes: Acquire multiple digital intermediate frequency interference signals; Spectral analysis is performed on each of the digital intermediate frequency interference signals to obtain signal spectrum analysis results, which include the angle, bandwidth, amplitude, and number of interference signals. Based on the signal spectrum analysis results, the subband filter structure is adjusted so that the number of interferences in any subband meets the interference suppression requirement. Each of the digital intermediate frequency interference signals is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal. Each sub-band signal is input into an adaptive interference suppression structure, and the signal spectrum analysis results are used for the initial calculation of the optimal weight vector to obtain the synthesized signal; The adjustment of the sub-band filter structure based on the signal spectrum analysis results includes: Based on the minimum bandwidth of the second subband signal and the number of interferences within the subband, the order of the subband filter is set to be greater than the number of interferences within the subband. Based on the minimum bandwidth of the second subband signal, the tap interval of the subband filter is set, where the tap interval D = fs / B, and fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

2. The adaptive interference suppression method based on spectrum analysis as described in claim 1, characterized in that, The step of performing spectral analysis on each of the digital intermediate frequency interference signals to obtain the signal spectral analysis results includes: Perform a fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time-domain signals to the frequency domain, and obtain the corresponding multi-channel sub-band signals. Perform a modulus-square operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal. Based on the power spectrum, a threshold is used to determine whether there is an interference signal in each of the sub-band signals. All sub-band signals with interfering signals are divided into frequency bandwidths to the minimum bandwidth. Signal processing is performed on all sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

3. The adaptive interference suppression method based on spectrum analysis as described in claim 1, characterized in that, The step of inputting each of the digital intermediate frequency interference signals into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal one includes: The digital intermediate frequency interference signals from each channel are converted from time-domain signals to frequency-domain signals by fast Fourier transform. Each of the digital intermediate frequency interference signals in the frequency domain is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal.

4. The adaptive interference suppression method based on spectrum analysis as described in claim 1, characterized in that, The method further includes: The synthesized signal is subjected to inverse fast Fourier transform to convert the frequency domain signal to the time domain for back-end processing.

5. An adaptive interference suppression system based on spectrum analysis, characterized in that, The system includes: Interference signal generation module, used to generate multiple digital intermediate frequency interference signals; The spectrum analysis module is used to perform spectrum analysis on each of the digital intermediate frequency interference signals to obtain the signal spectrum analysis results, which include the angle, bandwidth, amplitude and number of interference signals. The filter adjustment module is used to adjust the sub-band filter structure based on the signal spectrum analysis results. Each of the digital intermediate frequency interference signals is input into the adjusted sub-band filter to obtain the corresponding multi-channel sub-band signal. An adaptive interference suppression module is used to use the signal spectrum analysis results for the initial calculation of the optimal weight vector, and to synthesize each of the sub-band signals to obtain a synthesized signal. The filter adjustment module includes: The order setting unit is used to set the order of the subband filter to be greater than the number of interferences in the subband, based on the minimum bandwidth of the second subband signal and the number of interferences in the subband. The tap interval setting unit is used to set the tap interval of the subband filter according to the minimum bandwidth of the second subband signal, wherein the tap interval D = fs / B, where fs is the sampling rate and B is the minimum bandwidth of the second subband signal.

6. The adaptive interference suppression system based on spectrum analysis as described in claim 5, characterized in that, The interference signal generation module includes a receiving array antenna, a radio frequency front end, and an analog-to-digital conversion circuit. The output of the receiving array antenna is connected to the radio frequency front end, and the output of the radio frequency front end is connected to the analog-to-digital conversion circuit; The output of the analog-to-digital conversion circuit is connected to the spectrum analysis module and the adaptive interference suppression structure, respectively.

7. The adaptive interference suppression system based on spectrum analysis as described in claim 5, characterized in that, The spectrum analysis module includes a first FFT module, a modulus-squared module, a sub-band division module, a threshold determination module, and a signal angle prediction module, wherein: The first FFT module is used to perform fast Fourier transform on each of the digital intermediate frequency interference signals to convert the time domain signal to the frequency domain and obtain the corresponding multi-subband signal. The modulus squaring module is used to perform a modulus squaring operation on one of the sub-band signals to obtain the power spectrum of the sub-band signal. The sub-band division module is used to determine whether there is an interference signal in each sub-band signal 2 based on the power spectrum and the threshold determination module, and to divide the frequency bandwidth of all sub-band signals 2 with interference signals to the minimum bandwidth. The signal angle prediction module is used to perform signal processing on all sub-band signals divided to the minimum bandwidth to obtain the signal spectrum analysis results.

8. The adaptive interference suppression system based on spectrum analysis as described in claim 5, characterized in that, The system also includes an IFFT module, which performs an inverse fast Fourier transform on the synthesized signal to convert the frequency domain signal to the time domain for back-end processing.

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