Satellite-borne SAR narrow-band interference suppression method

Abstract

The invention discloses a satellite-borne SAR narrow-band interference suppression method, and relates to the technical field of satellite-borne SAR, and the method comprises the steps: carrying out the feature decomposition of an original echo signal, constructing a feature beam, and judging whether the maximum value of the feature beam is located in an antenna main lobe range or not, and accurately recognizing the feature vector and feature value of a narrow-band interference signal; constructing a whitening matrix to perform whitening processing on the original echo signal, and removing signal correlation; an approximation function is constructed based on the ultra-Gaussian distribution characteristics of narrow-band interference, and narrow-band interference signal samples are analyzed, processed and separated by using independent components; and finally, constructing an orthogonal projection matrix according to the sample, and carrying out orthogonal projection processing on an original echo signal to effectively suppress narrowband interference. The method has better interference identification accuracy and suppression performance, the SAR imaging quality can be remarkably improved, and image artifacts caused by interference are eliminated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of spaceborne synthetic aperture radar, and particularly relates to a spaceborne SAR narrowband interference suppression method. BACKGROUND

[0002] Spaceborne Synthetic Aperture Radar (SAR) payload obtains remote sensing data by transmitting and receiving electromagnetic waves. However, the complex electromagnetic environment on the earth's surface poses a challenge to the anti-interference capability of the spaceborne SAR payload. With the development of spaceborne synthetic aperture radar (SAR) systems towards high resolution, the receiving bandwidth of the system has reached the order of several GHz. This wide receiving characteristic makes the SAR echo extremely susceptible to narrowband interference in the complex electromagnetic environment on the earth's surface. In addition, the electromagnetic environment on the earth's surface is complex, and multiple transmission sources overlap with the working frequency of the SAR payload, further increasing the risk of interference. If the SAR payload lacks anti-interference measures, the system may lose the ability to obtain information when encountering electromagnetic interference. Therefore, the anti-interference capability of the SAR system is crucial, and narrowband interference suppression has always been a key research area in the field of spaceborne SAR. Narrowband interference has a instantaneous bandwidth less than 1% of the radar bandwidth, presents a multi-frequency point comb distribution characteristic in the frequency domain, and propagates along a single path, resulting in a power significantly higher than that of normal echoes. This type of interference overlaps with SAR echo signals in time domain, frequency domain and spatial domain, and if effective suppression measures are not taken, the SAR system will completely lose the ability to obtain information, and serious "bright line" artifacts will be produced in the imaging results, greatly reducing the image quality.

[0003] To solve the above problems, existing engineering applications mainly use non-parametric interference suppression algorithms, including three mainstream technologies: adaptive filter, notch filter and subspace projection algorithm. Among them, the least mean square (LMS) adaptive filter realizes signal separation by constructing a frequency domain, time domain or spatial domain filter, and performs well in the single interference source scenario; the notch filter realizes interference suppression by introducing transmission zeros in the interference frequency band, and is suitable for the case where interference only occupies a small part of the spectrum; the subspace projection algorithm constructs a projection matrix based on the extracted interference samples to realize interference cancellation, and can overcome the limitations of the first two methods.

[0004] However, the existing technology still has obvious defects. The convergence speed and robustness of the LMS filter are significantly limited when facing time-varying interference or interference sources with stronger sidelobes. The notch filter must set a wide zero region to suppress multiple interference sources when dealing with multi-frequency point narrowband interference, which will destroy the signal spectrum integrity and cause the sidelobe level to rise after pulse compression. The performance of the subspace projection algorithm is severely dependent on the independence of the interference samples, and if there is coupling between the interference samples, residual interference will be produced after projection processing, affecting the suppression effect.

[0005] Therefore, the existing narrow-band interference suppression technology is difficult to balance the convergence speed, multi-interference processing capability and suppression performance under the complex electromagnetic environment, and cannot meet the strict requirements of the high-resolution space-borne SAR system on the interference suppression effect, and a new technical method is urgently needed to break through the above bottleneck. SUMMARY

[0006] The technical problem to be solved by the present application is to overcome the deficiencies of the prior art, specifically to solve the problem of imaging quality degradation caused by narrow-band interference of space-borne SAR under complex electromagnetic environment, and specifically to provide a space-borne SAR narrow-band interference suppression method, which is as follows: 1) In a first aspect, the present application provides a space-borne SAR narrow-band interference suppression method, and the specific technical solutions are as follows: S1, performing feature decomposition on the original echo signal received by the space-borne SAR load to obtain a plurality of first feature vectors; constructing a feature beam based on each first feature vector, and determining the second feature vector of the narrow-band interference signal and its corresponding eigenvalue according to the relationship between the spatial angle corresponding to the maximum value in all feature beams and the main lobe range of the antenna; S2, constructing a whitening matrix according to the second feature vector and its corresponding eigenvalue, and performing whitening processing on the original echo signal based on the whitening matrix to obtain whitened echo data; S3, constructing an approximate function based on the characteristics of the narrow-band interference signal, and processing the echo data using the approximate function to obtain a narrow-band interference signal sample; S4, constructing an orthogonal projection matrix according to the narrow-band interference signal sample, and performing orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain an expected echo signal after narrow-band interference suppression.

[0007] The space-borne SAR narrow-band interference suppression method provided by the present application has the following beneficial effects: Through feature extraction and feature beam construction, the difference in spatial distribution characteristics between the narrow-band interference and the expected echo is utilized to accurately identify the feature vector and eigenvalue corresponding to the narrow-band interference signal, thereby improving the accuracy of interference detection. The approximate function is constructed based on the characteristics of the narrow-band interference signal, which is more consistent with the super-Gaussian distribution characteristics of the narrow-band interference, and the signal correlation is removed through whitening processing, which can improve the separation performance of the interference sample by the subsequent independent component analysis and reduce the residual interference. The original echo signal is processed through the orthogonal projection matrix, which can effectively suppress the narrow-band interference signal, improve the signal-to-interference ratio, eliminate the bright lines caused by narrow-band interference in the SAR image, and significantly improve the imaging quality.

[0008] On the basis of the above-mentioned scheme, the present application can also be improved as follows.

[0009] Further, the S1 specifically comprises: S101, obtain raw data received by a space-borne SAR load, and parse the raw data to obtain raw echo signals; S102, calculate an autocorrelation matrix of the raw echo signals, and perform eigenvalue decomposition on the autocorrelation matrix to obtain a plurality of first eigenvectors and corresponding eigenvalues thereof; S103, sequentially construct a corresponding characteristic beam based on each first eigenvector, and find a spatial angle corresponding to a maximum value in each characteristic beam; S104, if the spatial angle is within a range of a main lobe of an antenna, it is determined that the first eigenvector corresponding to the spatial angle is a second eigenvector of a narrow-band interference signal, and the corresponding eigenvalue is an eigenvalue of the narrow-band interference signal.

[0010] Further, a whitening matrix is constructed according to the second eigenvector and the corresponding eigenvalue, specifically including: S201, constructing an eigenvector matrix by using the second eigenvector, and constructing an eigenvalue matrix by using the corresponding eigenvalue of the second eigenvector; S202, constructing the whitening matrix according to the eigenvector matrix and the eigenvalue matrix.

[0011] Further, the S3 specifically includes: S301, constructing an approximation function based on a super-Gaussian distribution characteristic of the narrow-band interference signal, and initializing a separation matrix; S302, performing an iterative operation on the echo data, updating the separation matrix by using derivative information of the approximation function, and stopping until the separation matrix converges; S303, separating the narrow-band interference signal sample from the echo data by using the converged separation matrix.

[0012] 2) In a second aspect, the application further provides a space-borne SAR narrow-band interference suppression system, and a specific technical solution is as follows, including: an interference identification module, a whitening processing module, a sample separation module, and an interference suppression module; The interference identification module is used for performing eigenvalue decomposition on raw echo signals received by a space-borne SAR load to obtain a plurality of first eigenvectors, constructing a characteristic beam based on each first eigenvector, and determining a second eigenvector of a narrow-band interference signal and a corresponding eigenvalue thereof according to a relationship between a spatial angle corresponding to a maximum value in all characteristic beams and a range of a main lobe of an antenna; The whitening processing module is used for constructing a whitening matrix according to the second eigenvector and the corresponding eigenvalue thereof, performing whitening processing on the raw echo signals based on the whitening matrix, and obtaining whitened echo data; The sample separation module is used for constructing an approximation function based on a characteristic of the narrow-band interference signal, processing the echo data by using the approximation function, and obtaining a narrow-band interference signal sample. The interference suppression module is configured to construct an orthogonal projection matrix according to the narrowband interference signal sample, and perform orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain a narrowband interference-suppressed expected echo signal.

[0013] Based on the above scheme, the application can be further improved as follows.

[0014] Further, the interference identification module specifically comprises: Obtaining original data received by a space-borne SAR load, and parsing the original data to obtain an original echo signal; Calculating an autocorrelation matrix of the original echo signal, and performing eigenvalue decomposition on the autocorrelation matrix to obtain a plurality of first eigenvectors and corresponding eigenvalues thereof; Constructing a corresponding characteristic beam based on each first eigenvector in sequence, and finding a spatial angle corresponding to a maximum value in each characteristic beam; If the spatial angle is located within a main lobe range of the antenna, it is determined that the first eigenvector corresponding to the spatial angle is a second eigenvector of the narrowband interference signal, and the corresponding eigenvalue is an eigenvalue of the narrowband interference signal.

[0015] Further, a whitening matrix is constructed according to the second eigenvector and the corresponding eigenvalue thereof, specifically comprising: An eigenvector matrix is constructed using the second eigenvector, and an eigenvalue matrix is constructed using the eigenvalue corresponding to the second eigenvector; The whitening matrix is constructed according to the eigenvector matrix and the eigenvalue matrix.

[0016] Further, the sample separation module specifically comprises: An approximate function is constructed based on the super-Gaussian distribution characteristics of the narrowband interference signal, and a separation matrix is initialized; The echo data is subjected to iterative operation, and the separation matrix is updated using derivative information of the approximate function until the separation matrix converges; The separation matrix after convergence is used to separate the narrowband interference signal sample from the echo data.

[0017] 3) In a third aspect, the application further provides a computer device, which comprises a processor, the processor is coupled with a memory, the memory stores at least one computer program, the at least one computer program is loaded and executed by the processor, so that the computer device realizes any one of the above methods.

[0018] 4) In a fourth aspect, the present invention also provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to enable a computer to implement any of the above methods.

[0019] It should be noted that the beneficial effects of the technical solutions of the second to fourth aspects of the present invention and their corresponding possible implementations can be found in the above description of the technical effects of the first aspect and its corresponding possible implementations, and will not be repeated here. Attached Figure Description

[0020] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating the steps of a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention. Figure 2 This is a schematic diagram showing the comparison of SAR signal spectra before and after narrowband interference suppression in a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention. Figure 3 This is a schematic diagram of the SAR image before interference suppression processing in a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the SAR image after interference suppression processing according to a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention; Figure 5 This is a schematic diagram comparing a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention with other interference methods; Figure 6 This is a structural block diagram of a computer device according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0022] like Figure 1 As shown in the figure, a spaceborne SAR narrowband interference suppression method according to an embodiment of the present invention includes the following steps: S1, perform feature decomposition on the original echo signal received by the spaceborne SAR payload to obtain multiple first feature vectors; construct feature beams based on each first feature vector, and determine the second feature vector of the narrowband interference signal and its corresponding feature value according to the relationship between the spatial angle corresponding to the maximum value among all feature beams and the range of the antenna main lobe. S2, constructing a whitening matrix according to the second eigenvector and the corresponding eigenvalue, and performing whitening processing on the original echo signal based on the whitening matrix to obtain echo data after whitening; S3, constructing an approximation function based on the characteristics of the narrowband interference signal, and processing the echo data using the approximation function to obtain a narrowband interference signal sample; S4, constructing an orthogonal projection matrix according to the narrowband interference signal sample, and performing orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain an expected echo signal after narrowband interference suppression.

[0023] The star-borne SAR narrowband interference suppression method provided by the application has the following beneficial effects: By feature extraction and feature beam construction, the difference between the narrowband interference and the expected echo in the spatial distribution characteristics can be used to accurately identify the eigenvector and eigenvalue corresponding to the narrowband interference signal, thereby improving the accuracy of interference detection. Based on the characteristics of the narrowband interference signal, an approximation function is constructed, which is more consistent with the super-Gaussian distribution characteristics of the narrowband interference, and cooperates with the whitening processing to remove the signal correlation, thereby improving the separation performance of the subsequent independent component analysis on the interference sample and reducing the residual interference. By performing orthogonal projection processing on the original echo signal through the orthogonal projection matrix, the narrowband interference signal can be effectively suppressed, the signal-to-interference ratio can be improved, the bright line caused by the narrowband interference in the SAR image can be eliminated, and the imaging quality can be significantly improved.

[0024] It should be noted that, in order to facilitate understanding, the technical terms appearing in the present scheme will be explained one by one, and subsequent details will not be repeated: Spaceborne SAR: refers to a spaceborne synthetic aperture radar (Spaceborne Synthetic Aperture Radar), which is an active remote sensing payload that acquires remote sensing data by transmitting and receiving electromagnetic waves.

[0025] Narrowband interference: refers to an interference signal with an instantaneous bandwidth less than 1% of the radar bandwidth, which presents a multi-frequency point comb-shaped distribution in the frequency domain, and the power is higher than the normal SAR echo, and the time domain, frequency domain and space domain all overlap with the SAR echo.

[0026] Original echo signal : refers to an echo signal obtained by analyzing the original data received by the SAR payload within the synthetic aperture time, which contains a mixture of expected echoes and narrowband interference.

[0027] First eigenvector: refers to all eigenvectors obtained by performing eigenvalue decomposition on the original echo signal.

[0028] Feature beam: refers to a spatial response function constructed based on the eigenvector, which is used to analyze the spatial angle characteristics of the signal.

[0029] Spatial angle: refers to the direction angle corresponding to the maximum value of the feature beam.

[0030] Antenna main lobe range: refers to the spatial angle range covered by the main lobe of the antenna pattern, used to identify the signal source.

[0031] Second feature vector: refers to the feature vector determined to belong to the narrowband interference signal after spatial angle identification.

[0032] Whitening matrix: refers to a transformation matrix constructed using the feature vector and eigenvalue of the narrowband interference signal (i.e. the second feature vector and its corresponding eigenvalue), used to remove the correlation between signals.

[0033] Whitening processing: refers to the decorrelation transformation of the original echo signal by the whitening matrix, to obtain the whitened echo data.

[0034] Characteristic of the narrowband interference signal: in this embodiment, refers to the super-Gaussian distribution characteristic of the narrowband interference signal.

[0035] Approximation function: refers to a nonlinear function constructed based on the characteristic of the narrowband interference signal, used for independent component analysis processing of the echo data.

[0036] Narrowband interference signal sample : refers to the narrowband interference signal component separated from the mixed signal by independent component analysis.

[0037] Orthogonal projection matrix: refers to a projection operator constructed using the narrowband interference signal sample, used to eliminate the interference component in the original echo signal.

[0038] Orthogonal projection processing: refers to the interference elimination operation of the original echo signal by the orthogonal projection matrix.

[0039] Desired echo signal: refers to the pure SAR echo signal obtained after narrowband interference suppression, used for subsequent imaging processing.

[0040] In another embodiment of the present scheme, the specific implementation of S1 is: S101, obtaining the original data received by the spaceborne SAR payload within the synthetic aperture time and parsing to obtain the original echo signal.

[0041] S102, calculating the autocorrelation matrix of the original echo signal , the expression is: ; Wherein, represents the expectation processing, represents the conjugate transposition processing.

[0042] Performing eigenvalue decomposition on the autocorrelation matrix to obtain M eigenvectors the first eigenvector) and its corresponding eigenvalue , the expression is: ; wherein, M is the order of the autocorrelation matrix .

[0043] S103, sequentially construct the corresponding eigenbeam based on each first eigenvector, specifically multiply the conjugate transpose of the first eigenvector with the azimuth vector to obtain the expression of the eigenbeam, the azimuth vector is a function of the azimuth angle. Construct the eigenbeam based on the mth first eigenvector , the expression is: , ; wherein, is the conjugate transpose of the first eigenvector , is the azimuth vector, is the azimuth angle.

[0044] By finding the maximum value of the eigenbeam and determining its corresponding spatial angle, it is judged whether the spatial angle is located within the main lobe range of the antenna. Find the maximum value of the eigenbeam , the expression is: ; wherein, is the maximum calculation, is the spatial angle corresponding to the maximum value of the eigenbeam.

[0045] S104, if is located within the main lobe range of the antenna, it is judged that is the eigenvector of the narrowband interference signal (i.e. the second eigenvector), and its corresponding eigenvalue is the eigenvalue of the narrowband interference signal, if it is located within the main lobe range, it is determined that the corresponding first eigenvector belongs to the second eigenvector of the narrowband interference signal, and the corresponding eigenvalue is the eigenvalue of the narrowband interference signal. Repeat the above eigenbeam construction and judgment process to traverse all M eigenvectors, finally determine K second eigenvectors of the narrowband interference signal and eigenvalues, wherein K is the number of detected narrowband interference signals, arrange these narrowband interference eigenvectors in columns to construct an eigenvector matrix, construct an eigenvalue diagonal matrix (i.e. an eigenvalue matrix) with the corresponding eigenvalues as the diagonal elements, complete the determination of the second eigenvector of the narrowband interference signal and its corresponding eigenvalue.

[0046] In another embodiment of the present scheme, the specific implementation of S2 is: ​S201, construct an eigenvector matrix by arranging the second eigenvectors of the narrowband interference signal determined in step S1 column-wise. The expression is: ; Where K is the number of second eigenvectors belonging to narrowband interference signals.

[0047] Construct an eigenvalue diagonal matrix using its corresponding eigenvalues ​​as diagonal elements. (i.e., the eigenvalue matrix), expressed as: ; in, To construct a diagonal matrix. It should be noted that in S201... as well as With S102 as well as Each represents an eigenvector matrix. and eigenvalue matrix The difference lies in the eigenvector matrix in S201. and eigenvalue matrix Constructed from the second eigenvector and its corresponding eigenvalue, with order K, representing the number of second eigenvectors belonging to the narrowband interference signal, and the eigenvector matrix in S102. and eigenvalue matrix Constructed from the first eigenvector and its corresponding eigenvalue, with an order of M, indicating that it contains M first eigenvectors.

[0048] S202, perform a power-of-negative operation on the eigenvalue diagonal matrix (i.e., the eigenvalue matrix) to obtain its inverse square root matrix. Multiply this inverse square root matrix by the conjugate transposed rank of the eigenvector matrix to obtain the whitening matrix. The expression is: ; in, This is for order conversion.

[0049] S203, whitening matrix Left-multiply the original echo signal After whitening, echo data with removed signal correlation (i.e., after whitening) is obtained. The expression is: .

[0050] In another embodiment of this solution, S3 is specifically implemented as follows: S301, Construct a new super-Gaussian distribution approximation function based on the super-Gaussian distribution characteristics of narrowband interference signals. The expression is: ; The function is implemented by hyperbolic cosine logarithmic operation on independent components and contains a normal number adjustment parameter, and then the separation matrix of independent component analysis is initialized as an M-order unit matrix, and the expression is: ; S302, iterative operation is carried out on the whitened echo data to gradually optimize the separation matrix, and the iterative process expression is: ; In each iteration, the first order derivative and second order derivative information of the approximation function are used to update and correct the separation matrix combined with the statistical expectation of the whitened echo data, and the iteration termination condition is set to reach the preset number and the separation matrix converges. S303, after the iteration is completed, the whitened echo signal is linearly transformed using the finally converged separation matrix , and the narrowband interference signal sample is extracted from the demixing result of the mixed signal, and the expression is: .

[0051] In another embodiment of the present scheme, the specific implementation of S4 is: S401, the narrowband interference signal sample obtained by separation in the S3 step is used to construct an orthogonal projection matrix , and the expression is: ; It should be noted that in S102 represents conjugate transpose processing, and here represents an orthogonal projection matrix. Although there is repetition in the use of letters, the use formats are different, so there will be no unclear expression.

[0052] S402, then the orthogonal projection matrix is left multiplied by the original echo signal to perform orthogonal projection operation, and by eliminating the interference components in the original echo signal related to the narrowband interference signal sample , the expected echo signal after narrowband interference suppression is finally output , and the expression is: .

[0053] Further, S1 specifically includes: S101, obtaining the original data received by the spaceborne SAR load, and parsing the original data to obtain the original echo signal; ​S102, calculate the autocorrelation matrix of the original echo signal, and perform eigenvalue decomposition on the autocorrelation matrix to obtain a plurality of first eigenvectors and corresponding eigenvalues; S103, sequentially constructing a corresponding feature beam based on each first eigenvector, and finding a spatial angle corresponding to a maximum value in each feature beam; S104, if the spatial angle is within the range of the main lobe of the antenna, determining that the first eigenvector corresponding to the spatial angle is a second eigenvector of the narrowband interference signal, and the corresponding eigenvalue is the eigenvalue of the narrowband interference signal.

[0054] Further, a whitening matrix is constructed according to the second eigenvector and the corresponding eigenvalue, specifically including: S201, constructing an eigenvector matrix using the second eigenvector, and constructing an eigenvalue matrix using the eigenvalue corresponding to the second eigenvector; S202, constructing a whitening matrix according to the eigenvector matrix and the eigenvalue matrix.

[0055] Further, S3 specifically includes: S301, constructing an approximation function based on the super-Gaussian distribution characteristics of the narrowband interference signal; and initializing a separation matrix; S302, performing iterative operation on the echo data, updating the separation matrix using the derivative information of the approximation function until the separation matrix converges; S303, separating the narrowband interference signal sample from the echo data using the converged separation matrix.

[0056] In the experiment, the hardware platform is a ThinkPad notebook computer, the CPU is an AMD RYZEN 7 series, the Win10 operating system, and the software platform is MATLAB2023b. The experiment uses X-band SAR satellite measured data.

[0057] The effectiveness and superiority of the spaceborne SAR narrowband interference suppression method of the application are verified by two experiments. Experiment 1 verifies the effectiveness of the method by comparing the frequency domain echo signal and SAR image before and after the method. Experiment 2 proves the superiority of the method by comparing the processing results of the method and the conventional method.

[0058] Experiment 1, Figure 2 The schematic diagram of the comparison results of the SAR signal spectrum before and after the narrowband interference suppression by the method of the application is shown, the red line represents the signal spectrum before the narrowband interference suppression, and the green line represents the signal spectrum after the narrowband interference suppression by the method of the application. Figure 3 and Figure 4 are respectively the schematic diagrams of the SAR image before and after the interference suppression processing, Figure 3The narrow-band interference causes the "bright line" in the SAR image before the narrow-band interference suppression, which affects the image quality. Figure 4 The "bright line" caused by the narrow-band interference is suppressed in the SAR image after the method of the application, and the image quality is improved.

[0059] Experiment 2, Figure 5 The schematic diagram of the comparison between the method of the application and other interference methods is shown, the blue line represents the time-domain waveform of the signal after the narrow-band interference suppression by the prior art method, and the green line represents the time-domain waveform of the signal after the narrow-band interference suppression by the method of the application.

[0060] Compared with the prior art, the application has the following advantages: The feature vector and the feature value of the narrow-band interference signal to be suppressed are determined by using the feature beam method; the newly constructed approximate function is more consistent with the super high stiffness of the narrow-band interference, and the separation performance of the interference samples can be improved, so that better interference suppression performance can be obtained.

[0061] In the above embodiments, although the steps are numbered S1, S2, etc., it is only a specific embodiment given by the application, and those skilled in the art can adjust the execution order of S1, S2, etc. according to the actual situation, and these situations are also within the protection scope of the application. It can be understood that in some embodiments, some or all of the above embodiments can be included.

[0062] The application also provides a spaceborne SAR narrow-band interference suppression system, and the specific technical scheme is as follows, which comprises: an interference identification module, a whitening processing module, a sample separation module and an interference suppression module. The interference identification module is used for performing feature decomposition on the original echo signal received by the spaceborne SAR load to obtain a plurality of first feature vectors; a feature beam is constructed based on each first feature vector, and the second feature vector of the narrow-band interference signal and the corresponding feature value are determined according to the relationship between the spatial angle corresponding to the maximum value in all feature beams and the main lobe range of the antenna. The whitening processing module is used for constructing a whitening matrix according to the second feature vector and the corresponding feature value, and performing whitening processing on the original echo signal based on the whitening matrix to obtain whitened echo data. The sample separation module is used for constructing an approximate function based on the characteristics of the narrow-band interference signal, and processing the echo data by using the approximate function to obtain the narrow-band interference signal sample. The interference suppression module is used for constructing an orthogonal projection matrix according to the narrow-band interference signal sample, and performing orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain the expected echo signal after the narrow-band interference suppression.

[0063] Based on the above scheme, the application can be further improved as follows.

[0064] Further, the interference identification module specifically comprises: Obtaining raw data received by the space-borne SAR load, and parsing the raw data to obtain raw echo signals; Calculating the autocorrelation matrix of the raw echo signals, and performing eigenvalue decomposition on the autocorrelation matrix to obtain a plurality of first eigenvectors and corresponding eigenvalues thereof; Consequently, constructing a corresponding characteristic beam based on each first eigenvector, and finding a spatial angle corresponding to a maximum value in each characteristic beam; If the spatial angle is within the range of the main lobe of the antenna, it is determined that the first eigenvector corresponding to the spatial angle is a second eigenvector of the narrowband interference signal, and the corresponding eigenvalue is an eigenvalue of the narrowband interference signal.

[0065] Further, a whitening matrix is constructed according to the second eigenvector and the corresponding eigenvalue, specifically comprising: An eigenvector matrix is constructed using the second eigenvector, and an eigenvalue matrix is constructed using the eigenvalue corresponding to the second eigenvector; The whitening matrix is constructed according to the eigenvector matrix and the eigenvalue matrix.

[0066] Further, the sample separation module specifically comprises: An approximate function is constructed based on the super-Gaussian distribution characteristics of the narrowband interference signal, and a separation matrix is initialized; The echo data is subjected to iterative operation, and the derivative information of the approximate function is used to update the separation matrix until the separation matrix converges; The narrowband interference signal sample is separated from the echo data using the converged separation matrix.

[0067] It should be noted that the beneficial effects of the space-borne SAR narrowband interference suppression system provided in the above embodiments are the same as those of the above space-borne SAR narrowband interference suppression method, and will not be repeated here. In addition, when the system provided in the above embodiments implements its functions, only the division of the above functional modules is taken as an example for illustration, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the system is divided into different functional modules according to actual conditions to complete all or part of the above described functions. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process is described in detail in the method embodiments, which will not be repeated here.

[0068] As Figure 6As shown, the computer device 300 according to an embodiment of the present application includes a processor 320 coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the computer device 300 implements any of the above methods, in particular: The computer device 300 can be different in configuration or performance, and can include one or more processors 320 (Central Processing Units, CPUs) and one or more memories 310, wherein the one or more memories 310 store at least one computer program 330, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the computer device 300 implements the above-described spaceborne SAR narrowband interference suppression method provided by the embodiments. Of course, the computer device 300 can also have a wired or wireless network interface, a keyboard, an input and output interface, and other components for realizing device functions, and the like, so as to perform input and output, and the computer device 300 can also include other components for realizing device functions, which are not described here.

[0069] The computer readable storage medium according to an embodiment of the present application stores at least one computer program, and the at least one computer program is loaded and executed by a processor, so that a computer implements any of the above methods.

[0070] Optionally, the computer readable storage medium can be a Read-Only Memory (ROM), a Random Access Memory (RAM), a Compact Disc Read-Only Memory (CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0071] In the exemplary embodiments, a computer program product or computer program is also provided, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes any of the above spaceborne SAR narrowband interference suppression methods.

[0072] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application are used to distinguish similar objects, and represent no particular order or sequence. The order of use of similar objects can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described.

[0073] Those skilled in the art will understand that the application can be implemented as a system, method or computer program product. Therefore, the present disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, microcode, etc.) or a combination of both software and hardware embodiments, which can all generally be referred to herein as a "circuit," "module" or "system." Furthermore, the present disclosure can take the form of a program product on one or more computer-readable medium(s) having computer-readable program code embodied in the medium.

[0074] Any combination of one or more computer-readable medium(s) can be utilized. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium can be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

[0075] Although the embodiments of the present application have been shown and described above, it is understood that the above-described embodiments are exemplary, and are not to be interpreted as limiting the present application, and that variations, modifications, substitutions and changes can be made by those skilled in the art without departing from the scope of the present application.

Claims

1. A method for suppressing narrowband interference in spaceborne SAR, characterized in that, include: S1, perform feature decomposition on the original echo signal received by the spaceborne SAR payload to obtain multiple first feature vectors; construct feature beams based on each first feature vector, and determine the second feature vector of the narrowband interference signal and its corresponding feature value according to the relationship between the spatial angle corresponding to the maximum value among all feature beams and the range of the antenna main lobe. S2, construct a whitening matrix based on the second feature vector and its corresponding feature value, and perform whitening processing on the original echo signal based on the whitening matrix to obtain whitened echo data; S3. Construct an approximation function based on the characteristics of the narrowband interference signal, and use the approximation function to process the echo data to obtain narrowband interference signal samples. S4. Construct an orthogonal projection matrix based on the narrowband interference signal sample, and perform orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain the desired echo signal after narrowband interference suppression.

2. The method for suppressing narrowband interference in spaceborne SAR according to claim 1, characterized in that, S1 specifically includes: S101, acquire the raw data received by the spaceborne SAR payload, and parse the raw data to obtain the raw echo signal; S102, calculate the autocorrelation matrix of the original echo signal, and perform eigenvalue decomposition on the autocorrelation matrix to obtain multiple first eigenvectors and their corresponding eigenvalues; S103, construct the corresponding feature beams based on each first feature vector in turn, and find the spatial angle corresponding to the maximum value in each feature beam; S104, if the spatial angle is within the range of the antenna main lobe, then the first feature vector corresponding to the spatial angle is determined to be the second feature vector of the narrowband interference signal, and its corresponding feature value is the feature value of the narrowband interference signal.

3. The method for suppressing narrowband interference in spaceborne SAR according to claim 1, characterized in that, Constructing a whitening matrix based on the second eigenvector and its corresponding eigenvalues ​​specifically includes: S201, construct an eigenvector matrix using the second eigenvector, and construct an eigenvalue matrix using the eigenvalues ​​corresponding to the second eigenvector; S202, construct a whitening matrix based on the eigenvector matrix and the eigenvalue matrix.

4. The method for suppressing narrowband interference in spaceborne SAR according to claim 1, characterized in that, S3 specifically includes: S301, Construct an approximate function based on the super-Gaussian distribution characteristics of narrowband interference signals; Initialize the separation matrix; S302, perform iterative calculations on the echo data, and update the separation matrix using the derivative information of the approximation function until the separation matrix converges; S303, using the converged separation matrix to separate narrowband interference signal samples from the echo data.

5. A spaceborne SAR narrowband interference suppression system, characterized in that, include: Interference identification module, whitening processing module, sample separation module, and interference suppression module; The interference identification module is used to perform feature decomposition on the original echo signal received by the spaceborne SAR payload to obtain multiple first feature vectors; construct feature beams based on each first feature vector; and determine the second feature vector of the narrowband interference signal and its corresponding feature value according to the relationship between the spatial angle corresponding to the maximum value among all feature beams and the range of the antenna main lobe. The whitening processing module is used to construct a whitening matrix based on the second feature vector and its corresponding feature value, and to perform whitening processing on the original echo signal based on the whitening matrix to obtain whitened echo data. The sample separation module is used to construct an approximation function based on the characteristics of the narrowband interference signal, and to process the echo data using the approximation function to obtain narrowband interference signal samples. The interference suppression module is used to construct an orthogonal projection matrix based on the narrowband interference signal samples, and to perform orthogonal projection processing on the original echo signal based on the orthogonal projection matrix to obtain the desired echo signal after narrowband interference suppression.

6. The spaceborne SAR narrowband interference suppression system according to claim 5, characterized in that, The interference identification module specifically includes: Acquire the raw data received by the spaceborne SAR payload, and parse the raw data to obtain the raw echo signal; Calculate the autocorrelation matrix of the original echo signal, and perform eigenvalue decomposition on the autocorrelation matrix to obtain multiple first eigenvectors and their corresponding eigenvalues; Construct corresponding feature beams based on each first feature vector in turn, and find the spatial angle corresponding to the maximum value in each feature beam; If the spatial angle is within the range of the antenna's main lobe, then the first feature vector corresponding to that spatial angle is determined to be the second feature vector of the narrowband interference signal, and its corresponding feature value is the feature value of the narrowband interference signal.

7. The spaceborne SAR narrowband interference suppression system according to claim 5, characterized in that, Constructing a whitening matrix based on the second eigenvector and its corresponding eigenvalues ​​specifically includes: Construct an eigenvector matrix using the second eigenvector, and construct an eigenvalue matrix using the eigenvalues ​​corresponding to the second eigenvector; A whitening matrix is ​​constructed based on the eigenvector matrix and the eigenvalue matrix.

8. A spaceborne SAR narrowband interference suppression system according to claim 5, characterized in that, The sample separation module specifically includes: An approximate function is constructed based on the super-Gaussian distribution characteristics of narrowband interference signals; the separation matrix is ​​initialized. The echo data is iteratively processed, and the separation matrix is ​​updated using the derivative information of the approximation function until the separation matrix converges. Narrowband interference signal samples are separated from the echo data using the converged separation matrix.

9. A computer device, characterized in that, The computer device includes a processor coupled to a memory storing at least one computer program, which is loaded and executed by the processor to enable the computer device to perform the method as claimed in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer program, which is loaded and executed by a processor to enable the computer to perform the method as described in any one of claims 1 to 4.

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