Method and system for detecting echo jamming of distributed SAR system of multi-satellite close formation distribution

Abstract

This invention provides a method and system for echo interference detection in a multi-satellite close-range formation distributed SAR system. Specifically, it includes: first, inputting raw echo data from the multi-satellite close-range formation distributed SAR system, assuming the system has M satellites; then, performing channel equalization on the raw echo data and transforming it to the azimuth time-range frequency domain; extracting azimuth and range samples from the processed results; then, detecting time-continuous narrowband interference using a covariance matrix constructed based on the azimuth samples; detecting broadband interference using a covariance matrix constructed based on the range samples; then, fusing the interference detection results; and finally, outputting the final interference detection result. This invention solves the problem of echo interference detection in multi-satellite close-range formation distributed SAR systems and provides important support for on-board and ground-based imaging processing in such systems.

Description

Technical Field

[0001] This invention relates to the field of radar signal processing technology, specifically to a method and system for detecting echo interference in a multi-satellite close-range formation distributed SAR system, and more specifically to a method and system for detecting echo interference in a multi-satellite close-range formation distributed SAR system based on covariance eigenvalue decomposition. Background Technology

[0002] Synthetic Aperture Radar (SAR) can perform all-weather, all-time, wide-area, high-resolution imaging of the Earth, and has become an important tool for Earth remote sensing. Multi-satellite close-range distributed SAR systems, through simultaneous Earth observation by multiple satellites in formation, can achieve high-precision topographic mapping and high-resolution 3D imaging, effectively improving Earth observation performance and attracting widespread attention and research in recent years.

[0003] However, with the increasing number of ground-based electronic devices, ground-based radio frequency interference (RFI) has become a major problem in distributed SAR imaging, posing a significant obstacle to raw data acquisition, imaging processing, and subsequent interpretation. This includes affecting the echo signal acquisition process and amplitude dynamic range, impacting interferometric altimetry accuracy, and 3D imaging focusing processing, severely affecting the performance of 3D SAR imaging and applications. Since RFI detection is a prerequisite for RFI suppression, RFI detection technology is currently one of the key technologies for 3D SAR ground data processing.

[0004] Existing patent literature and papers propose radio frequency interference detection methods, which have many shortcomings. For example, they do not consider the coherence of interference between multiple satellites, multi-satellite systems, and multi-satellite formation distributed SAR imaging applications, which makes it impossible to achieve optimal detection of interference in multi-satellite formation distributed SAR systems, or to apply them to multi-satellite formation distributed SAR imaging systems.

[0005] In summary, there is currently no effective and universally applicable interference detection method for multi-satellite close-range formation distributed SAR systems. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention aims to propose an interference detection method and system for multi-satellite close-range formation distributed SAR systems based on covariance matrix eigenvalue decomposition, effectively solving the interference detection problem and improving the performance of 3D SAR satellite imaging.

[0007] A method for detecting echo interference in a multi-satellite close-range formation distributed SAR system according to the present invention includes:

[0008] Input steps: Input raw echo data from a multi-satellite close-range formation distributed SAR system, and set the multi-satellite close-range formation distributed SAR system to include M satellites;

[0009] Channel equalization step: Equalize the raw echo data channels of each satellite to obtain the channel equalized raw echo data;

[0010] Narrowband detection steps: Based on the original echo data after channel equalization, extract azimuth samples, and use the covariance matrix constructed from the azimuth samples to detect time-continuous narrowband interference, and obtain the narrowband interference detection result.

[0011] Broadband detection steps: Based on the raw echo data after channel equalization, range samples are extracted. Broadband interference is detected by constructing the covariance matrix using the range samples, and the broadband interference detection results are obtained.

[0012] Detection fusion step: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection result.

[0013] Preferably, in the channel equalization step, the original echo data is first subjected to amplitude and phase equalization processing using an internal calibration and data adaptive processing algorithm. Amplitude and phase equalization includes in-band equalization and inter-satellite amplitude equalization.

[0014] Preferably, in the channel equalization step, the equalization of the raw echo data channels of each satellite includes inter-satellite echo equalization and in-band equalization within the effective signal bandwidth of a single satellite.

[0015] Preferably, the narrowband detection step includes the following sub-steps:

[0016] Step S1: Transform the raw echo data after channel equalization to the azimuth time domain-range frequency domain, and set the SAR echo signal of the m-th satellite as s. m (t a ,f), where ta is the azimuth time and f is the signal frequency;

[0017] Step S2: For all frequency units f, construct the covariance matrix using azimuth samples respectively.

[0018]

[0019] In the formula, s(t) a ,f)=[s1(t a ,f)s2(t a ,f)…s M (t a ,f)] TThe superscripts “T” and “H” represent transpose and conjugate transpose, respectively; N is the number of azimuth samples; and PRT is the pulse repetition period.

[0020] Step S3: Place C s (t a f) Perform eigenvalue decomposition and set the maximum eigenvalue as λ1;

[0021] Step S4: Fit the maximum eigenvalue λ1 of different distance frequencies:

[0022]

[0023] In the formula, σ is the parameter to be fitted, Γ(N) is the gamma function, and N is the number of samples;

[0024] Step S5: Set the false alarm threshold λ0 based on the Rayleigh distribution parameter fitting results;

[0025] Step S6: When the largest eigenvalue λ1 of the covariance matrix of the frequency unit f is ≥ λ0, the unit is considered to have interference, i.e., the narrowband interference detection result F nb (t a If f) = 1, then it is considered that there is no interference, i.e., the narrowband interference detection result F is 1. nb (t a ,f)=0.

[0026] Preferably, the broadband detection step includes the following sub-steps:

[0027] Step T1: Transform the raw echo data after channel equalization to the azimuth time domain-range frequency domain, and define the SAR echo signal of the m-th satellite as s. m (t a ,f), where ta is the azimuth time and f is the signal frequency;

[0028] Step T2: For all azimuth times t a Covariance matrices are constructed from the frequency samples respectively.

[0029]

[0030] In the formula, s(t) a ,f)=[s1(t a ,f)s2(t a ,f)…s M (t a ,f)] T The superscripts “T” and “H” represent transpose and conjugate transpose, respectively, N is the number of frequency samples, and Δf is the frequency interval between adjacent frequency units.

[0031] Step T3: Place C s (ta Perform eigenvalue decomposition on f, assuming the largest eigenvalue is λ2;

[0032] Step T4: Fit the maximum eigenvalue λ2 at different azimuth times:

[0033]

[0034] In the formula, σ is the parameter to be fitted, Γ(N) is the gamma function, and N is the number of samples;

[0035] Step T5: Set the false alarm threshold λ0 based on the Rayleigh distribution parameter fitting results;

[0036] Step T6: When the azimuth time t a When the largest eigenvalue λ2 of the covariance matrix is ​​≥ λ0, the cell is considered to have interference, i.e., the broadband interference detection result F wb (t a If f) = 1, then it is considered that there is no interference, i.e., the broadband interference detection result F is 1. wb (t a ,f)=0.

[0037] Preferably, in step S4, during the process of fitting the maximum eigenvalue distribution function using the Rayleigh distribution, the units containing interference are eliminated iteratively.

[0038] Preferably, the detection fusion step includes the following sub-steps:

[0039] Step U1: Initial fusion interference detection result is

[0040] F(t a ,f)=F nb (t a ,f)+(1-F nb (t a ,f))·F wb (t a f)

[0041] In the formula, F(t) a f) represents the initial fusion interference detection result, F nb (t a f) represents the narrowband interference detection result, F wb (t a f) represents the broadband interference detection result;

[0042] Step U2: Correct the initial fusion interference detection results using the line detection method to obtain the final interference detection results.

[0043] Preferably, in the detection fusion step, the final interference detection result is output for use in interference suppression processing.

[0044] This invention also provides a system for detecting echo interference in a multi-satellite close-range formation distributed SAR system, comprising:

[0045] Module M1: Input raw echo data from a multi-satellite close-range formation distributed SAR system, which is set to include M satellites;

[0046] Module M2: Equalizes the raw echo data channels of each satellite to obtain the raw echo data after channel equalization;

[0047] Module M3: Based on the original echo data after channel equalization, azimuth samples are extracted. The covariance matrix constructed from the azimuth samples is used to detect time-continuous narrowband interference and obtain the narrowband interference detection results.

[0048] Module M4: Based on the original echo data after channel equalization, range samples are extracted. The covariance matrix constructed from the range samples is used to detect broadband interference and obtain the broadband interference detection results.

[0049] Module M5: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection result.

[0050] The present invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described method for detecting echo interference in a multi-satellite close-range formation distributed SAR system.

[0051] Compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. This invention is the first to address the interference suppression problem in multi-satellite close-range formation distributed SAR systems. It detects interference by using the maximum eigenvalue of the covariance matrix, effectively improving the interference-to-signal ratio and thus enhancing the interference detection accuracy. This invention effectively solves the echo interference detection problem in multi-satellite close-range formation distributed SAR systems and provides important support for the mapping and 3D imaging of multi-satellite formation distributed SAR systems.

[0053] 2. This invention utilizes the coherence between interference received by a multi-satellite close-range array distributed SAR system to achieve interference coherence accumulation and improve the interference-to-signal ratio. This overcomes the problem of low interference-to-signal ratio and difficulty in detecting interference in traditional single-satellite processing, and improves the performance of interference detection and suppression. Attached Figure Description

[0054] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0055] Figure 1This is a schematic diagram of the interference detection and processing flow in an embodiment of the present invention;

[0056] Figure 2a It is satellite A in the interference suppression SAR images of the first two satellites in this embodiment of the invention;

[0057] Figure 2b It is satellite B in the interference suppression SAR images of the first two satellites in this embodiment of the invention;

[0058] Figure 3a It is satellite A in the two-satellite SAR image after interference suppression in the embodiment of the present invention;

[0059] Figure 3b It is satellite B in the two-satellite SAR image after interference suppression in the embodiment of the present invention. Detailed Implementation

[0060] This invention provides a method and system for echo interference detection in a multi-satellite close-range formation distributed SAR system. Specifically, it includes: first, inputting raw echo data from the multi-satellite close-range formation distributed SAR system, assuming the system has M satellites; then, performing channel equalization on the raw echo data and transforming it to the azimuth time-range frequency domain; extracting azimuth and range samples from the processed results; then, detecting time-continuous narrowband interference using a covariance matrix constructed based on the azimuth samples; detecting broadband interference using a covariance matrix constructed based on the range samples; then, fusing the interference detection results; and finally, outputting the final interference detection result. This invention solves the problem of echo interference detection in multi-satellite close-range formation distributed SAR systems and provides important support for on-board and ground-based imaging processing in such systems.

[0061] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the scope of protection of the present invention.

[0062] Example 1:

[0063] Figure 1 This is a schematic diagram of the interference detection and processing flow in an embodiment of the present invention.

[0064] like Figure 1 As shown, this embodiment of the invention provides a method for detecting echo interference in a multi-satellite close-range formation distributed SAR system, including:

[0065] Input steps: Input raw echo data from a multi-satellite close-range formation distributed SAR system, which includes M satellites.

[0066] Channel equalization step: Equalize the raw echo data channels of each satellite to obtain the channel-equalized raw echo data.

[0067] Due to the influence of non-ideal factors such as electromechanical and thermal properties, the channel equalization process first uses an internal calibration and data adaptive processing algorithm to perform amplitude and phase equalization on the original echo data. Amplitude and phase equalization includes in-band equalization and inter-satellite amplitude equalization.

[0068] Specifically, the equalization of the raw echo data channels of each satellite includes the equalization of inter-satellite echoes and the in-band equalization within the effective signal bandwidth of a single satellite.

[0069] Narrowband detection steps: Based on the original echo data after channel equalization, azimuth samples are extracted. The covariance matrix constructed from the azimuth samples is used to detect time-continuous narrowband interference, and the narrowband interference detection result is obtained.

[0070] Specifically, the narrowband detection step includes the following sub-steps:

[0071] Step S1: Transform the raw echo data after channel equalization to the azimuth time domain-range frequency domain, and set the SAR echo signal of the m-th satellite as s. m (t a ,f), where ta is the azimuth time and f is the signal frequency.

[0072] Step S2: For all frequency units f, construct the covariance matrix using azimuth samples respectively.

[0073]

[0074] In the formula, s(t) a ,f)=[s1(t a ,f)s2(t a ,f)…s M (t a ,f)] T The superscripts “T” and “H” represent transpose and conjugate transpose, respectively, N is the number of azimuth samples, and PRT is the pulse repetition period.

[0075] Step S3: Place C s (t a f) Perform eigenvalue decomposition and set the maximum eigenvalue as λ1.

[0076] For interference-free echo signals, the echo signals received by each satellite will be completely decorrelated, and theoretically, their eigenvalues ​​should all be equal and equal to the signal energy. If interference is present, the interference signals received by each satellite should be completely correlated. In this case, after eigenvalue decomposition, the largest eigenvalue is the sum of the signal energy and the interference energy.

[0077] Step S4: Fit the maximum eigenvalue λ1 of different distance frequencies:

[0078]

[0079] In the formula, σ is the parameter to be fitted, Γ(N) is the gamma function, and N is the number of samples.

[0080] Specifically, in the process of fitting the maximum eigenvalue distribution function using the Rayleigh distribution, the impact of interference on the accuracy of parameter fitting is reduced by iteratively eliminating the units containing interference.

[0081] Step S5: Set the false alarm threshold λ0 based on the Rayleigh distribution parameter fitting results.

[0082] Step S6: When the largest eigenvalue λ1 of the frequency element f covariance matrix is ​​≥ λ0, the element is considered to have interference, i.e., the narrowband interference detection result F nb (t a If f) = 1, then it is considered that there is no interference, i.e., the narrowband interference detection result F is 1. nb (t a ,f)=0.

[0083] Broadband detection steps: Based on the original echo data after channel equalization, range samples are extracted. Broadband interference is detected by constructing the covariance matrix using the range samples, and the broadband interference detection results are obtained.

[0084] Specifically, the broadband detection steps include the following sub-steps:

[0085] Step T1: Transform the raw echo data after channel equalization to the azimuth time domain-range frequency domain, and define the SAR echo signal of the m-th satellite as s. m (t a ,f), where ta is the azimuth time and f is the signal frequency.

[0086] Step T2: For all azimuth times t a The covariance matrix is ​​constructed from the frequency of the samples respectively.

[0087]

[0088] In the formula, s(t) a ,f)=[s1(t a ,f)s2(t a,f)…s M (t a ,f)] T The superscripts “T” and “H” represent transpose and conjugate transpose, respectively, N is the number of frequency samples, and Δf is the frequency interval between adjacent frequency units.

[0089] Step T3: Place C s (t a Perform eigenvalue decomposition on f, and set the maximum eigenvalue to λ2.

[0090] For interference-free echo signals, the echo signals received by each satellite will be completely decorrelated, and theoretically, their eigenvalues ​​should all be equal and equal to the signal energy. If interference is present, the interference signals received by each satellite should be completely correlated. In this case, after eigenvalue decomposition, the largest eigenvalue is the sum of the signal energy and the interference energy.

[0091] Step T4: Fit the maximum eigenvalue λ2 at different azimuth times:

[0092]

[0093] In the formula, σ is the parameter to be fitted, Γ(N) is the gamma function, and N is the number of samples.

[0094] Step T5: Set the false alarm threshold λ0 based on the Rayleigh distribution parameter fitting results.

[0095] Step T6: When the azimuth time t a When the largest eigenvalue λ2 of the covariance matrix is ​​≥ λ0, the cell is considered to have interference, i.e., the broadband interference detection result F wb (t a If f) = 1, then it is considered that there is no interference, i.e., the broadband interference detection result F is 1. wb (t a ,f)=0.

[0096] Detection fusion step: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection result.

[0097] Specifically, the detection fusion step includes the following sub-steps:

[0098] Step U1: Initial fusion interference detection result is

[0099] F(t a ,f)=F nb (t a ,f)+(1-F nb (t a ,f))·F wb (t a f)

[0100] In the formula, F(t) a f) represents the initial fusion interference detection result, F nb (t a f) represents the narrowband interference detection result, F wb (t a f) represents the broadband interference detection result.

[0101] Step U2: Correct the initial fusion interference detection results using the line detection method to obtain the final interference detection results.

[0102] In the detection and fusion step, the final interference detection results are output for use in interference suppression processing.

[0103] Example 2:

[0104] This invention also provides a system for detecting echo interference in a multi-satellite close-range formation distributed SAR system. The system for detecting echo interference in a multi-satellite close-range formation distributed SAR system can be implemented by executing the process steps of the method for detecting echo interference in a multi-satellite close-range formation distributed SAR system. That is, those skilled in the art can understand the method for detecting echo interference in a multi-satellite close-range formation distributed SAR system as a preferred embodiment of the system for detecting echo interference in a multi-satellite close-range formation distributed SAR system.

[0105] This embodiment of a system for detecting echo interference in a multi-satellite close-range formation distributed SAR system includes:

[0106] Module M1: Input raw echo data from a multi-satellite close-range formation distributed SAR system, which is set to include M satellites;

[0107] Module M2: Equalizes the raw echo data channels of each satellite to obtain the raw echo data after channel equalization;

[0108] Module M3: Based on the original echo data after channel equalization, azimuth samples are extracted. The covariance matrix constructed from the azimuth samples is used to detect time-continuous narrowband interference and obtain the narrowband interference detection results.

[0109] Module M4: Based on the original echo data after channel equalization, range samples are extracted. The covariance matrix constructed from the range samples is used to detect broadband interference and obtain the broadband interference detection results.

[0110] Module M5: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection result.

[0111] Example 3:

[0112] This embodiment provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the method for detecting echo interference in a multi-satellite close-range formation distributed SAR system described in Embodiment 1 above.

[0113] The following uses measured data from the Land Detection-1 01 group of satellites to verify the method for detecting echo interference in a multi-satellite close-range distributed SAR system provided by this invention.

[0114] The LuTan-1 01 group of satellites is a two-satellite formation system with a center frequency of 1.26 GHz and a signal bandwidth of 80 MHz. Figure 2a , Figure 2b These are satellites A and B, representing SAR images acquired by the first two satellites after interference suppression. Figure 3a , Figure 3b These are satellites A and B, respectively, after notch filtering interference suppression using the detection results provided by this invention. Figure 3a and Figure 3b It can be seen that the interference was effectively suppressed after processing by the method proposed in this invention.

[0115] Those skilled in the art will understand that, besides implementing the system and its various devices, modules, and units provided by this invention in the form of purely computer-readable program code, the same functions can be achieved entirely through logical programming of the method steps, making the system and its various devices, modules, and units of this invention function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, the system and its various devices, modules, and units provided by this invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be considered as structures within the hardware component; alternatively, the devices, modules, and units for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0116] In the description of this application, it should be understood that the terms "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0117] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for detecting echo interference in a multi-satellite close-range formation distributed SAR system, characterized in that, include: Input steps: Input raw echo data from a multi-satellite close-range formation distributed SAR system, and set the multi-satellite close-range formation distributed SAR system to include M satellites; Channel equalization step: Equalize the raw echo data channels of each satellite to obtain the channel equalized raw echo data; Narrowband detection steps: Based on the original echo data after channel equalization, extract azimuth samples, and use the covariance matrix constructed from the azimuth samples to detect time-continuous narrowband interference, thereby obtaining the narrowband interference detection result. Broadband detection steps: Based on the original echo data after channel equalization, range samples are extracted. Broadband interference is detected using the covariance matrix constructed from the range samples to obtain the broadband interference detection result. Detection fusion step: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection result; The narrowband detection step includes the following sub-steps: Step S1: Transform the original echo data after channel equalization to the azimuth time domain-range frequency domain, and set the SAR echo signal of the m-th satellite as... ,in, For location and time, The signal frequency; Step S2: For all frequency units Covariance matrices were constructed using azimuth samples respectively. In the formula, The superscripts "T" and "H" indicate transpose and conjugate transpose, respectively. This represents the number of samples in the azimuth direction. The pulse repetition period; Step S3: Perform eigenvalue decomposition and set the maximum eigenvalue as . ; Step S4: Calculate the maximum eigenvalues ​​at different distance frequencies. Perform fitting: In the formula, The parameters to be fitted are... For gamma function, The number of samples; Step S5: Set the false alarm threshold based on the Rayleigh distribution parameter fitting results. ; Step S6: When the frequency unit Maximum eigenvalue of covariance matrix ≥ If the signal is invalid, the unit is considered to have interference, i.e., the narrowband interference detection result is invalid. Conversely, if no interference is detected, it is considered that there is no interference, i.e., the narrowband interference detection result is negative. ; The broadband detection step includes the following sub-steps: Step T1: Transform the original echo data after channel equalization to the azimuth time domain-range frequency domain, and define the SAR echo signal of the m-th satellite as... ,in, For location and time, The signal frequency; Step T2: For all orientation times The covariance matrix is ​​constructed from the frequency of the samples respectively. In the formula, The superscripts "T" and "H" indicate transpose and conjugate transpose, respectively. For frequency to sample number, The frequency interval between adjacent frequency units; Step T3: Put Perform eigenvalue decomposition, assuming the largest eigenvalue is... ; Step T4: Calculate the maximum eigenvalue at different azimuth times. Perform fitting: In the formula, The parameters to be fitted are... For gamma function, The number of samples; Step T5: Set the false alarm threshold based on the Rayleigh distribution parameter fitting results. ; Step T6: When the azimuth time The largest eigenvalue of the covariance matrix ≥ If the signal is invalid, the unit is considered to be experiencing interference, i.e., the broadband interference detection result is invalid. Conversely, if no interference is detected, it is considered that no interference exists, i.e., the broadband interference detection result is... ; The detection fusion step includes the following sub-steps: Step U1: Initial fusion interference detection result is In the formula, The initial fusion interference detection results, This is the result of narrowband interference detection. This is the result of broadband interference detection; Step U2: Correct the initial fusion interference detection result using the line detection method to obtain the final interference detection result.

2. The method for detecting echo interference in a multi-satellite close-range formation distributed SAR system according to claim 1, characterized in that, In the channel equalization step, the original echo data is first subjected to amplitude and phase equalization processing using an internal calibration and data adaptive processing algorithm. The amplitude and phase equalization includes in-band equalization and inter-satellite amplitude equalization.

3. The method for detecting echo interference in a multi-satellite close-range formation distributed SAR system according to claim 1, characterized in that, In the channel equalization step, the equalization of the raw echo data channels of each satellite includes the equalization of inter-satellite echoes and the in-band equalization within the effective signal bandwidth of a single satellite.

4. The method for detecting echo interference in a multi-satellite close-range formation distributed SAR system according to claim 1, characterized in that, In step S4, during the process of fitting the maximum eigenvalue distribution function using Rayleigh distribution, the units containing interference are iteratively eliminated.

5. The method for detecting echo interference in a multi-satellite close-range formation distributed SAR system according to claim 1, characterized in that, In the detection fusion step, the final interference detection result is output for use in interference suppression processing.

6. A system for implementing the method for echo interference detection in a multi-satellite close-range formation distributed SAR system as described in claim 1, characterized in that, include: Module M1: Input raw echo data from a multi-satellite close-range formation distributed SAR system, wherein the multi-satellite close-range formation distributed SAR system comprises M satellites; Module M2: Equalizes the raw echo data channels of each satellite to obtain the raw echo data after channel equalization; Module M3: Based on the original echo data after channel equalization, extract azimuth samples, and use the covariance matrix constructed from the azimuth samples to detect time-continuous narrowband interference, thereby obtaining the narrowband interference detection result; Module M4: Based on the original echo data after channel equalization, range samples are extracted, and broadband interference is detected using the covariance matrix constructed from the range samples to obtain broadband interference detection results; Module M5: Based on the narrowband interference detection results and the broadband interference detection results, the interference detection results are fused to obtain the final interference detection results.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for detecting echo interference in a multi-satellite close-range formation distributed SAR system as described in any one of claims 1 to 5.

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