Inter-satellite direct wave interference suppression method and system for synthetic aperture radar satellites

Abstract

The invention provides an inter-satellite direct wave interference suppression method and system for synthetic aperture radar satellites. The method comprises the following steps: inputting SAR original echo data and system parameters thereof; calculating a pulse repetition frequency, a signal bandwidth and a frequency modulation rate; performing matched filtering and filtering on the original echo data to obtain an echo signal; and carrying out direct wave interference trapped wave processing and inverse matching filtering processing on the echo signal, and outputting original echo data after suppression processing. According to the method, signal self-correlation processing is adopted for detecting and suppressing the inter-satellite direct wave interference for the first time, the problem that an existing inter-satellite direct wave interference suppression processing method greatly depends on model applicability is solved, and important technical support is provided for subsequent large-scale SAR constellation earth imaging observation; direct wave interference is suppressed through a parameterization method, and the application effect of the SAR satellite in the fields of resource investigation, topographic mapping, disaster monitoring and the like is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite-borne radars, and in particular relates to a method and system for suppressing direct-arrival wave interference between synthetic aperture radar satellites. Background Art

[0002] Spaceborne synthetic aperture radar (SAR) is an active microwave imaging sensor based on a satellite platform. It achieves high-resolution imaging in range by transmitting broadband frequency-modulated signals and pulse compression technology, and in azimuth by using azimuth virtual synthetic aperture technology. Spaceborne SAR images contain rich geometric, radiometric, and phase information, and are the primary technical means for all-day, all-weather Earth observation. With the increasing number of SAR satellites in orbit in the same frequency band, the frequency of inter-satellite direct wave interference has increased, attracting widespread attention. This interference, characterized by long duration and large bandwidth, can seriously affect the quality of both spaceborne SAR images. There is an urgent need to conduct research on effective inter-satellite direct wave interference suppression technologies to improve the imaging quality and data reliability of SAR systems.

[0003] Direct waves differ from scattered waves. Scattered wave interference signals enter the receiver after being scattered by the ground, atmosphere, or objects. They may come from multiple directions, and their path delay and polarization characteristics change dynamically. In contrast, direct wave interference signals reach the SAR receiver via a direct path (no reflections). The interference source direction is fixed and predictable (such as the transmit beam of another satellite). Scattered interference typically covers a wider spatial and frequency domain and exhibits randomness (such as multipath effects or clutter superposition). In contrast, the delay, Doppler shift, and polarization characteristics of direct wave interference are relatively stable, and can be modeled as a point source or narrow beam signal. Therefore, the key to direct wave interference treatment lies in accurately locating the interference source and suppressing it by analyzing its temporal, spatial, and frequency characteristics.

[0004] The paper "SAR pulse direct wave interference suppression method using improved characteristic subspace projection" (Shu Gaofeng, Liu Mingyue, Li Ning. Journal of Electronics and Information Technology, 2024, 46(4): 1382-1390.) proposes an improved ESP SAR pulse direct wave interference suppression method for ground radar and communication direct wave interference. However, the method in this paper is a non-parametric method, and the interference suppression performance is closely related to the model.

[0005] The papers "On the Mutual Interference Between Spaceborne SARs: Modeling, Characterization, and Mitigation" (H. Yang, M. Tao, S. Chen, F. Xi and Z. Liu, IEEE Transactions on Geoscience and Remote Sensing, vol. 59, no. 10, pp. 8470-8485) and "Observation and Mitigation of Mutual RFI Between SAR Satellites: A Case Study Between Chinese GaoFen-3 and European Sentinel-1A" (N. Li, Z. Lv and Z. Guo, IEEE Transactions on Geoscience and Remote Sensing, vol. 60, pp. 1-19, 2022) respectively studied the problem of direct wave interference between SAR satellites and the characteristics of mutual radio frequency interference (MRFI) in SAR data, proposed an interference description and characterization model and a new RFI detection method based on spectral energy elimination (SEC), and proposed the use of principal component analysis (PCA) and robust principal component analysis (RPCA) to effectively suppress interference in the image domain. However, both of them are mainly aimed at the interference of inter-satellite ground direct waves, and have not yet considered the interference of inter-satellite direct waves.

[0006] The paper "Research on Intersatellite Terrain Scattering Interference for Spaceborne SAR Systems" (Tao Mingliang, Sun Huanyu, Liu Yanyang, et al. Information Countermeasures Technology, 2023, 2(3): 64-73.) introduces the intersatellite terrain scattering interference pattern of spaceborne SAR systems. Based on the difference in the signal models of ground direct interference and intersatellite scattering mutual interference, the characteristic differences of the two interferences in different signal representation domains are compared and analyzed. However, the problem of suppressing intersatellite direct wave interference has not yet been addressed.

[0007] The paper "Ultra-Wideband Mutual RFI Mitigation Between SAR Satellites: From the Perspective of European Sentinel-1A" (N. Li and X. Hu, IEEE Transactions on Geoscience and Remote Sensing) studies and analyzes the ultra-wideband MRFI characteristics of different C-band SAR satellites. It proposes an out-of-band spectral energy (OSE) detection method and an improved eigenvalue subspace projection (ESP) method, which can effectively address interference issues caused by complex spatial scene changes. However, this paper primarily addresses inter-satellite ground-based direct wave interference and does not consider inter-satellite direct wave interference.

[0008] The patent document "Method, System, Storage Medium, and Electronic Device for Suppressing Mutual Interference of Spaceborne Synthetic Aperture Radar Scattered Waves Based on Matched Filtering" (CN119535366A) discloses a method for effectively utilizing the compression gain of mutual interference to accurately extract the mutual interference signal from synthetic aperture radar echoes. This method effectively suppresses interference while better protecting the useful signal, significantly improving the quality of SAR images. However, the direct wave suppression effect and signal fidelity are poor, requiring further adaptation of interference parameter estimation, threshold setting, and sparsity constraints.

[0009] In summary, there is currently no parameterized method for suppressing inter-satellite direct wave interference (DWI) between SAR satellites. The performance of non-parametric methods is affected by model applicability, resulting in significant signal loss and difficulty suppressing DWI when the model is mismatched. A technology for suppressing DWI between satellites in large-scale SAR constellations is needed to significantly improve the effectiveness of SAR satellite applications in resource surveying, topographic mapping, disaster monitoring, and other fields. Summary of the Invention

[0010] In view of the defects in the prior art, the purpose of the present invention is to provide a method and system for suppressing direct wave interference between synthetic aperture radar satellites.

[0011] The method for suppressing direct-arrival wave interference between synthetic aperture radar satellites provided by the present invention comprises:

[0012] Step S1: inputting the SAR original echo data and system parameters affected by intersatellite direct wave interference;

[0013] Step S2: Calculate the pulse repetition frequency, signal bandwidth and modulation rate according to the original echo data;

[0014] Step S3: performing matched filtering and filtering on the original echo data according to the signal bandwidth and modulation frequency to obtain the echo signal;

[0015] Step S4: performing direct wave interference notch processing and inverse matching filter processing on the echo signal to obtain the suppressed original echo data;

[0016] Step S5: Output the suppressed original echo data.

[0017] Preferably, step S2 includes:

[0018] Step S2.1: The original echo data are grouped into M original echoes at different azimuth times, and the original echo data are rearranged to obtain rearranged echo data E1.

[0019] Step S2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the pulse repetition frequency of the direct wave interference.

[0020] Step S2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation processing and transform it into the range frequency domain. The signal bandwidth B of the intersatellite direct wave interference is estimated according to the set detection threshold. r,I and center frequency f c,I .

[0021] Step S2.4: Use time-frequency analysis and range-directed autofocusing algorithm to estimate the modulation frequency K of the direct wave interference signal r,I .

[0022] Preferably, the step S2.3 includes:

[0023] Step S2.3.1: Set the autocorrelation function values outside the window of twice the width of the main lobe of the autocorrelation function around the secondary peak position n0 of the autocorrelation function to zero, and obtain the autocorrelation function F c,1 .

[0024] Step S2.3.2: Perform Fourier transformation on the autocorrelation function in the range direction, take the modulus value, and then average it in the azimuth direction to obtain the average value of the direct wave interference spectrum intensity.

[0025] Step S2.3.3: Set the detection threshold based on the average value of the direct wave interference spectrum intensity, and use the leading and trailing edges of the signal spectrum to determine the direct wave interference signal bandwidth B. r,I and center frequency f c,I .

[0026] Preferably, step S3 includes:

[0027] Step S3.1: Perform range compression on the original echo data E0 using the obtained signal bandwidth and frequency modulation rate.

[0028] Step S3.2: Detect the signal peak of the original echo data after range compression, and calculate the peak value according to the pulse repetition period PRI. IThe false peaks of the original echo data after range compression are eliminated to obtain the echo signal.

[0029] Preferably, step S4 includes:

[0030] Step S4.1: According to the obtained peak positions of all direct wave interference impulse response functions, the signal of the window with the peak position as the center and more than twice the width of the main lobe of the impulse response function is set to zero.

[0031] Step S4.2: Perform inverse matching filtering on the echo signal to obtain suppressed original echo data.

[0032] According to the present invention, a synthetic aperture radar satellite inter-satellite direct wave interference suppression system is provided, comprising:

[0033] Module M1: Input SAR original echo data and system parameters interfered by intersatellite direct waves;

[0034] Module M2: Calculates pulse repetition frequency, signal bandwidth and modulation rate based on the original echo data;

[0035] Module M3: performs matched filtering and filtering on the original echo data according to the signal bandwidth and modulation frequency to obtain the echo signal;

[0036] Module M4: performs direct wave interference notch processing and anti-matching filtering on the echo signal to obtain the suppressed original echo data;

[0037] Module M5: Outputs the suppressed original echo data.

[0038] Preferably, the module M2 includes:

[0039] Module M2.1: The original echo data are grouped into M azimuth time points, and the original echo data are rearranged to obtain rearranged echo data E1.

[0040] Module M2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the pulse repetition frequency of the direct wave interference.

[0041] Module M2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation processing and transform it to the range frequency domain. According to the set detection threshold, the signal bandwidth B of the intersatellite direct wave interference is estimated. r,I and center frequency f c,I .

[0042] Module M2.4: Estimating the modulation frequency K of the direct wave interference signal using time-frequency analysis and range-directed autofocusing algorithm r,I .

[0043] Preferably, the module M2.3 includes:

[0044] Module M2.3.1: Set the autocorrelation function values outside the window of twice the width of the main lobe of the autocorrelation function around the secondary peak position n0 of the autocorrelation function to zero, and obtain the autocorrelation function F c,1 .

[0045] Module M2.3.2: Perform Fourier transformation on the autocorrelation function in the range direction, take the modulus value, and then average it in the azimuth direction to obtain the average value of the direct wave interference spectrum intensity.

[0046] Module M2.3.3: Set the detection threshold based on the average value of the direct wave interference spectrum intensity, and use the leading and trailing edges of the signal spectrum to determine the direct wave interference signal bandwidth B r,I and center frequency f c,I .

[0047] Preferably, the module M3 includes:

[0048] Module M3.1: Use the obtained signal bandwidth and frequency modulation rate to perform range compression on the original echo data E0.

[0049] Module M3.2: Detect the signal peak of the original echo data after distance compression, according to the pulse repetition period PRI I The false peaks of the original echo data after range compression are eliminated to obtain the echo signal.

[0050] Preferably, the module M4 includes:

[0051] Module M4.1: According to the peak positions of all direct wave interference impulse response functions obtained, the signal of the window with the peak position as the center and more than twice the width of the main lobe of the impulse response function is set to zero.

[0052] Module M4.2: Perform inverse matching filtering on the echo signal to obtain the suppressed original echo data.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] 1. The present invention uses signal autocorrelation processing for the first time to detect and suppress inter-satellite direct wave interference, and estimates the inter-satellite interference signal parameters under the assumption of linear frequency modulation signals to achieve detection and suppression of inter-satellite direct wave interference.

[0055] 2. The present invention effectively solves the problem that existing inter-satellite direct wave interference suppression processing methods are highly dependent on model applicability, providing important technical support for subsequent large-scale SAR constellation earth imaging observations.

[0056] 3. The present invention suppresses direct wave interference through a parameterized method, significantly improving the application effect of SAR satellites in resource surveys, topographic mapping, disaster monitoring and other fields. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Other features, objects and advantages of the present invention will become more apparent upon reading the detailed description of non-limiting embodiments with reference to the following drawings:

[0058] Figure 1 This is a schematic diagram of the process of detecting and suppressing direct wave interference between SAR satellites;

[0059] Figure 2 Schematic diagram of correlation function of 10 pulses;

[0060] Figure 3 Schematic diagram of the range spectrum corresponding to the extracted correlation function peak;

[0061] Figure 4 Schematic diagram of the original SAR image interfered by intersatellite direct waves;

[0062] Figure 5 This is a schematic diagram of the SAR image after the SAR satellite inter-satellite direct wave interference is suppressed. DETAILED DESCRIPTION

[0063] The present invention will be described in detail below with reference to specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but are not intended to limit the present invention in any form. It should be noted that, for those skilled in the art, several changes and improvements can be made without departing from the scope of the present invention. These all fall within the scope of protection of the present invention.

[0064] According to the present invention, a method for suppressing direct-arrival interference between synthetic aperture radar satellites is provided. Based on the signal autocorrelation processing technology, the problem of suppressing direct-arrival interference between synthetic aperture radar (SAR) satellites is successfully solved, providing important technical support for the subsequent large-scale SAR constellation system construction. Figure 1 For example, it includes:

[0065] Step S1: Inputting the SAR original echo data and system parameters interfered by inter-satellite direct waves.

[0066] The SAR original echo data affected by the inter-satellite direct wave interference is selected by manual judgment or automatic judgment by the system.

[0067] Step S2: Estimate inter-satellite direct wave interference parameters such as pulse repetition frequency, signal bandwidth and frequency modulation rate.

[0068] Furthermore, the step S2 estimates inter-satellite direct wave interference parameters such as pulse repetition frequency, signal bandwidth and modulation frequency, including:

[0069] Step S2.1: Rearrange the original echo data into a group of M original echoes at different azimuth times, and record the rearranged echo data as E1;

[0070] Assume that the size of the original echo E0 is N a ×N r , N a 、N r are the number of points in the azimuth and distance directions respectively. The size of the rearranged data is N a1 ×N r1 , the element value in row m and column n is

[0071]

[0072] Where N r1 N is the number of distance points after rearrangement of the data. r1 =PRF·F s M, PRF is the pulse repetition frequency, F s is the range sampling rate, N r is the number of range points of the original echo of the original input, is the floor operator. N a1 is the number of samples.

[0073] Step S2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the repetition frequency of the direct wave interference pulse;

[0074] The functional relationship of autocorrelation processing is expressed as:

[0075] F c (m,:)=IFT{|FT{E1(m,:)}| 2}

[0076] Where FT{·} represents Fourier transform and IFT{·} represents inverse Fourier transform. Find the location of the secondary peak of the autocorrelation function, assuming it is n0, then the pulse repetition period of the direct wave interference, that is, the direct wave interference pulse repetition frequency is PRI I =n0 / F s PRI l represents the interference repetition period, F s The range sampling rate of a SAR satellite affected by intersatellite direct wave interference is shown in Figure 2. The column-wise autocorrelation of the rearranged data matrix is used to effectively amplify the secondary peak characteristics of periodic direct wave interference.

[0077] Step S2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation function, transform it into the range frequency domain, set the detection threshold to estimate the signal bandwidth B of the intersatellite direct wave interference r,I and center frequency f c,I ;

[0078] As an important parameter of interference, the center frequency is a necessary option for interference parameter estimation.

[0079] Furthermore, the step S2.3 includes:

[0080] Step S2.3.1: Set the autocorrelation function values outside a certain window around the secondary peak position n0 of the autocorrelation function to zero to obtain the autocorrelation function F c,1 , the window is usually selected to be more than twice the width of the main lobe of the autocorrelation function. c,1 Expressed as:

[0081]

[0082] Where W represents the window width, which is usually selected to be more than twice the width of the main lobe of the autocorrelation function and is adjusted according to actual needs.

[0083] Step S2.3.2: Perform Fourier transformation on the autocorrelation function in the distance direction and take the modulus value and then average it in the azimuth direction to obtain the average direct wave interference spectrum intensity. Expressed as:

[0084]

[0085] Where N a1 is the number of samples, and FT{·} represents Fourier transform.

[0086] Step S2.3.3: Set the detection threshold and use the leading and trailing edges of the signal spectrum to determine the bandwidth B of the direct wave interference signal. r,I and center frequency f c,I .

[0087] Assume that the detection threshold T is expressed as:

[0088]

[0089] Where α is the threshold coefficient, which is adjusted according to actual needs. After threshold detection, the leading and trailing edges of the signal spectrum are f start and f end , then the bandwidth of the direct wave interference signal is B r,I and center frequency f c,I Expressed as:

[0090] B r,I =fend -f start

[0091]

[0092] The periodic characteristics of the interference signal (such as pulse repetition frequency (PRF)) are extracted through the autocorrelation function, and the modulation frequency and bandwidth are estimated by combining time-frequency analysis to construct a parameterized interference signal model. This breaks through the applicability limitations of the model and can still maintain robustness when the interference signal parameters change dynamically.

[0093] Step S2.4: Use time-frequency analysis methods such as short-time Fourier transform (STFT) and phase gradient autofocusing (PGA) equidistance autofocusing algorithm to estimate the modulation frequency K of the direct wave interference signal r,I .

[0094] Step S3: Perform matched filtering and direct wave interference detection on the original echo.

[0095] Furthermore, the step S3 performs matched filtering on the original echo to detect direct wave interference, including:

[0096] Step S3.1: Perform range compression on the original echo E0 using the signal bandwidth and modulation rate estimated in step S2;

[0097] The matched filter response function is:

[0098]

[0099] Where K r,I 、B r,I 、f c,I Respectively represent the modulation frequency, signal bandwidth, and center frequency of the direct wave interference signal, f is the range frequency, and j represents an imaginary number. The matched filtering process is expressed as:

[0100] S range_comp,I =IFT(FT(S E0 (t a ,:)·F I (f))

[0101] Where S E0 Represents the signal of the original echo E0, S range_comp,I The signal representing the completion of distance compression. a Indicates the time of position, F I represents the matched filter response function.

[0102] Step S3.2: Detect the signal peak of the direct wave interference signal distance compression, according to the pulse repetition period PRI I The false peaks are eliminated at intervals to obtain the echo signal.

[0103] The coupled estimation of parameters such as PRF, bandwidth and modulation frequency is achieved through the joint processing of autocorrelation sub-peak location and range frequency domain spectrum analysis.

[0104] Step S4: performing direct wave interference notch processing on the echo signal after matched filtering, and performing inverse matched filtering processing.

[0105] Furthermore, the step S4 performs direct wave interference notch processing on the echo signal after matched filtering, and performs inverse matched filtering processing, including:

[0106] Step S4.1: Based on the peak positions of all direct wave interference impulse response functions obtained in step S3, the signal in a certain window (usually selected to be at least twice the width of the main lobe of the impulse response function) is set to zero with each peak position as the center to achieve direct wave interference suppression;

[0107] Assume that the peak position corresponding to a certain azimuth unit m1 is n1, and the process of setting the signal of a certain window around the peak position to zero is expressed as:

[0108]

[0109] Where S range_comp,c represents the signal after zeroing, W1 represents the interference suppression window width, which is usually selected to be more than twice the main lobe width of the impulse response function. It is adjusted according to actual needs and the above processing is performed on all azimuth units.

[0110] Step S4.2: performing inverse matched filtering on the original echo after matched filtering to obtain original echo data after interference suppression;

[0111] The inverse matching filter function is expressed as:

[0112]

[0113] Where K r,I 、B r,I 、f c,I They represent the modulation frequency, signal bandwidth, and center frequency estimation of the direct wave interference signal, and f is the range frequency.

[0114] The three-stage processing architecture of "matched filtering-notch filtering-anti-matched filtering" eliminates interference in the range-frequency domain. Compared with traditional time-domain nulling methods, this effectively reduces effective signal loss and improves the interference suppression ratio (ISR).

[0115] Step S5: Outputting the original echo data after interference suppression.

[0116] In more preferred examples, the original echo data of the Lutan-1 01 group of satellites is used to superimpose inter-satellite direct wave interference. Figure 2 The correlation functions of 10 pulses are given; Figure 3 The range spectrum corresponding to the peak of the extracted correlation function is given; Figure 4 The SAR imaging results before interference suppression are given; Figure 5 The SAR imaging results after interference suppression are shown. As can be seen from the figure, interference has been effectively suppressed, effectively solving the problems of model mismatch sensitivity, low parameter estimation accuracy, and large signal loss in existing methods, and providing reliable interference suppression for large-scale SAR constellation networking.

[0117] The present invention also provides a synthetic aperture radar satellite inter-satellite direct wave interference suppression system, which can be implemented by executing the process steps of the synthetic aperture radar satellite inter-satellite direct wave interference suppression method, that is, those skilled in the art can understand the synthetic aperture radar satellite inter-satellite direct wave interference suppression method as a preferred implementation of the synthetic aperture radar satellite inter-satellite direct wave interference suppression system.

[0118] According to the present invention, a synthetic aperture radar satellite inter-satellite direct wave interference suppression system is provided, comprising:

[0119] Module M1: Input SAR original echo data and system parameters interfered by intersatellite direct waves;

[0120] Module M2: Calculates pulse repetition frequency, signal bandwidth and modulation rate based on the original echo data;

[0121] Module M3: performs matched filtering and filtering on the original echo data according to the signal bandwidth and modulation frequency to obtain the echo signal;

[0122] Module M4: performs direct wave interference notch processing and anti-matching filtering on the echo signal to obtain the suppressed original echo data;

[0123] Module M5: Outputs the suppressed original echo data.

[0124] In more preferred embodiments, the module M2 includes:

[0125] Module M2.1: The original echo data are grouped into M azimuth time points, and the original echo data are rearranged to obtain rearranged echo data E1.

[0126] Module M2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the pulse repetition frequency of the direct wave interference.

[0127] Module M2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation processing and transform it to the range frequency domain. According to the set detection threshold, the signal bandwidth B of the intersatellite direct wave interference is estimated. r,I and center frequency f c,I .

[0128] Module M2.4: Estimating the modulation frequency K of the direct wave interference signal using time-frequency analysis and range-directed autofocusing algorithm r,I .

[0129] In more preferred embodiments, the module M2.3 includes:

[0130] Module M2.3.1: Set the autocorrelation function values outside the window of twice the width of the main lobe of the autocorrelation function around the secondary peak position n0 of the autocorrelation function to zero, and obtain the autocorrelation function F c,1 .

[0131] Module M2.3.2: Perform Fourier transformation on the autocorrelation function in the range direction, take the modulus value, and then average it in the azimuth direction to obtain the average value of the direct wave interference spectrum intensity.

[0132] Module M2.3.3: Set the detection threshold based on the average value of the direct wave interference spectrum intensity, and use the leading and trailing edges of the signal spectrum to determine the direct wave interference signal bandwidth B r,I and center frequency f c,I .

[0133] In more preferred embodiments, the module M3 includes:

[0134] Module M3.1: Use the obtained signal bandwidth and frequency modulation rate to perform range compression on the original echo data E0.

[0135] Module M3.2: Detect the signal peak of the original echo data after distance compression, according to the pulse repetition period PRI I The false peaks of the original echo data after range compression are eliminated to obtain the echo signal.

[0136] In more preferred embodiments, the module M4 includes:

[0137] Module M4.1: According to the peak positions of all direct wave interference impulse response functions obtained, the signal of the window with the peak position as the center and more than twice the width of the main lobe of the impulse response function is set to zero.

[0138] Module M4.2: Perform inverse matching filtering on the echo signal to obtain the suppressed original echo data.

[0139] Those skilled in the art will appreciate that, in addition to implementing the system and its various devices, modules, and units provided by the present invention in purely computer-readable program code, it is entirely possible to implement the same functions of the system and its various devices, modules, and units provided by the present invention in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered 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; the devices, modules, and units for implementing various functions can also be considered as both software modules implementing the method and structures within the hardware component.

[0140] The above describes specific embodiments of the present invention. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. The embodiments of this application and the features in the embodiments may be combined with each other in any manner unless there is a conflict.

Claims

1. A method for suppressing direct-arrival interference between synthetic aperture radar satellites, characterized in that: include: Step S1: inputting the SAR original echo data and system parameters affected by intersatellite direct wave interference; Step S2: Calculate the pulse repetition frequency, signal bandwidth and modulation rate according to the original echo data; Step S3: performing matched filtering and filtering on the original echo data according to the signal bandwidth and modulation frequency to obtain the echo signal; Step S4: performing direct wave interference notch processing and inverse matching filter processing on the echo signal to obtain the suppressed original echo data; Step S5: Output the suppressed original echo data.

2. The method for suppressing inter-satellite direct wave interference of synthetic aperture radar satellites according to claim 1, characterized in that: The step S2 comprises: Step S2.1: Rearrange the original echo data into groups of M original echoes at different azimuth times to obtain rearranged echo data E1; Step S2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the pulse repetition frequency of the direct wave interference; Step S2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation processing and transform it into the range frequency domain. The signal bandwidth B of the intersatellite direct wave interference is estimated based on the set detection threshold. r,I and center frequency f c,I ; Step S2.4: Use time-frequency analysis and range-directed autofocusing algorithm to estimate the modulation frequency K of the direct wave interference signal r,I .

3. The method for suppressing inter-satellite direct wave interference of synthetic aperture radar satellites according to claim 2, characterized in that: The step S2.3 includes: Step S2.3.1: Set the autocorrelation function values outside the window of twice the width of the main lobe of the autocorrelation function around the secondary peak position n0 of the autocorrelation function to zero, and obtain the autocorrelation function F c,1 ; Step S2.3.2: Perform Fourier transformation on the autocorrelation function in the range direction, take the modulus value, and then average it in the azimuth direction to obtain the average value of the direct wave interference spectrum intensity; Step S2.3.3: Set the detection threshold based on the average value of the direct wave interference spectrum intensity, and use the leading and trailing edges of the signal spectrum to determine the direct wave interference signal bandwidth B. r,I and center frequency f c,I .

4. The method for suppressing inter-satellite direct wave interference of synthetic aperture radar satellites according to claim 1, characterized in that: The step S3 comprises: Step S3.1: Perform range compression on the original echo data E0 using the obtained signal bandwidth and frequency modulation rate; Step S3.2: Detect the signal peak of the original echo data after range compression, and calculate the peak value according to the pulse repetition period PRI. I The false peaks of the original echo data after range compression are eliminated to obtain the echo signal.

5. The method for suppressing inter-satellite direct wave interference of synthetic aperture radar satellites according to claim 1, characterized in that: The step S4 comprises: Step S4.1: according to the obtained peak positions of all direct wave interference impulse response functions, set the signal of the window with the peak position as the center and the width of the main lobe of the impulse response function greater than twice to zero; Step S4.2: Perform inverse matching filtering on the echo signal to obtain suppressed original echo data.

6. A synthetic aperture radar satellite inter-satellite direct wave interference suppression system, characterized in that: include: Module M1: Input SAR original echo data and system parameters interfered by intersatellite direct waves; Module M2: Calculates pulse repetition frequency, signal bandwidth and modulation rate based on the original echo data; Module M3: performs matched filtering and filtering on the original echo data according to the signal bandwidth and modulation frequency to obtain the echo signal; Module M4: performs direct wave interference notch processing and anti-matching filtering on the echo signal to obtain the suppressed original echo data; Module M5: Outputs the suppressed original echo data.

7. The synthetic aperture radar satellite inter-satellite direct wave interference suppression system according to claim 6, characterized in that: The module M2 includes: Module M2.1: Rearrange the original echo data into groups of M azimuth times to obtain rearranged echo data E1; Module M2.2: Perform autocorrelation processing on the rearranged echo data column by column to extract the pulse repetition frequency of the direct wave interference; Module M2.3: Extract the response function area corresponding to the intersatellite direct wave in the autocorrelation processing and transform it to the range frequency domain. According to the set detection threshold, the signal bandwidth B of the intersatellite direct wave interference is estimated. r,I and center frequency f c,I ; Module M2.4: Estimating the modulation frequency K of the direct wave interference signal using time-frequency analysis and range-directed autofocusing algorithm r,I .

8. The synthetic aperture radar satellite inter-satellite direct wave interference suppression system according to claim 7, characterized in that: The module M2.3 includes: Module M2.3.1: Set the autocorrelation function values outside the window of twice the width of the main lobe of the autocorrelation function around the secondary peak position n0 of the autocorrelation function to zero, and obtain the autocorrelation function F c,1 ; Module M2.3.2: Perform Fourier transformation of the autocorrelation function in the range direction, take the modulus value, and then average it in the azimuth direction to obtain the average direct wave interference spectrum intensity; Module M2.3.3: Set the detection threshold based on the average value of the direct wave interference spectrum intensity, and use the leading and trailing edges of the signal spectrum to determine the direct wave interference signal bandwidth B r,I and center frequency f c,I .

9. The synthetic aperture radar satellite inter-satellite direct wave interference suppression system according to claim 6, characterized in that: The module M3 includes: Module M3.1: Use the obtained signal bandwidth and frequency modulation rate to perform distance compression on the original echo data E0; Module M3.2: Detect the signal peak of the original echo data after distance compression, according to the pulse repetition period PRI I The false peaks of the original echo data after range compression are eliminated to obtain the echo signal.

10. The synthetic aperture radar satellite inter-satellite direct wave interference suppression system according to claim 6, characterized in that: The module M4 includes: Module M4.1: Based on the peak positions of all direct wave interference impulse response functions obtained, set the signal of the window with the peak position as the center and the width of the main lobe of the impulse response function greater than twice to zero; Module M4.2: Perform inverse matching filtering on the echo signal to obtain the suppressed original echo data.

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