Azimuth ambiguity calculation method and system under spaceborne multi-channel SAR error conditions

Abstract

The present invention provides a method and system for calculating azimuth ambiguity under error conditions of a satellite-borne multi-channel SAR, comprising the following steps: Step 1: obtaining the azimuth ambiguity under error conditions of the satellite-borne multi-channel SAR; Step 2: optimizing the satellite-borne multi-channel SAR system according to the azimuth ambiguity, and obtaining the index requirements of the satellite-borne multi-channel SAR system under error conditions through iteration. The present invention calculates the satellite-borne multi-channel azimuth ambiguity based on echo simulation processing, and can superimpose various errors of the satellite-to-ground full link, effectively solving the problem of no accurate error model for azimuth ambiguity calculation of the satellite-borne multi-channel SAR, and has important guiding significance for the optimization design and engineering development of the satellite-borne multi-channel SAR system.

Description

Technical Field

[0001] The present invention relates to the technical field of azimuth ambiguity calculation, and in particular to a method and system for calculating azimuth ambiguity under satellite-borne multi-channel SAR error conditions. Background Art

[0002] The azimuth resolution and distance mapping bandwidth of spaceborne SAR are two mutually restrictive technical indicators. If the spaceborne SAR system wants to expand the mapping bandwidth, it needs to sacrifice the azimuth resolution, and vice versa. In order to alleviate the contradiction between high azimuth resolution and wide distance coverage, a variety of new technologies and new ideas have been proposed at home and abroad. Among them, the most classic and feasible is the use of azimuth multi-channel technology. Azimuth multi-channel technology uses the "Displaced Phase Centre Antenna (DPCA) principle" to significantly reduce the pulse repetition frequency of the SAR system, thereby improving the ambiguity index of the SAR system and achieving mapping bandwidth expansion under high-resolution conditions.

[0003] At the same time, the satellite-ground integration index is the core embodiment of the performance of the SAR satellite system. It is directly related to the application efficiency of the satellite system. Therefore, it has always been the focus of analysis and guarantee in the design and development of the SAR satellite system. Compared with the traditional satellite-borne single-channel SAR, the satellite-borne multi-channel SAR, as a new working system, has undergone major changes in the azimuth ambiguity (Azimuth Ambiguity to Signal Ratio, AASR) in the satellite-ground integration index. The traditional single-channel AASR calculation model is no longer applicable. NICOLAS GEBERT of Germany gave an approximate mathematical calculation model of satellite-borne multi-channel AASR in the article "Digital Beamforming on Receive: Techniques and Optimization Strategies for High-Resolution Wide-Swath SAR Imaging" and compared it with the simulation calculation. However, the article did not give the detailed steps and methods of the simulation calculation. In particular, the model did not consider various errors of the multi-channel system, and could not quantitatively calculate the azimuth ambiguity of the satellite-borne multi-channel SAR under the error condition.

[0004] With respect to the above-mentioned prior art, the inventors believe that the existing satellite-borne multi-channel SAR azimuth ambiguity calculation method has no error model and cannot quantitatively calculate the impact of various errors in the entire satellite-to-ground link on indicators. Summary of the invention

[0005] In view of the defects in the prior art, the object of the present invention is to provide a method and system for calculating the azimuth ambiguity under error conditions of a satellite-borne multi-channel SAR.

[0006] According to the present invention, a method for calculating azimuth ambiguity under error conditions of a space-borne multi-channel SAR is provided, comprising the following steps:

[0007] Step 1: Obtain the azimuth ambiguity under the error condition of the spaceborne multi-channel SAR;

[0008] Step 2: According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized, and the index requirements of the spaceborne multi-channel SAR system under the error condition are obtained through iteration.

[0009] Preferably, step 1 comprises the following steps:

[0010] Step 1.1: Set the number of fuzzy zones to obtain the number of azimuth sampling points;

[0011] Step 1.2: Generate a time domain azimuth echo signal with an ambiguous area under an error condition by simulation according to the azimuth sampling point number;

[0012] Step 1.3: performing spectrum shifting and Fourier transform on the time domain azimuth echo signal to obtain a frequency domain azimuth echo signal;

[0013] Step 1.4: Perform spectrum reconstruction processing on the frequency domain azimuth echo signal according to the multi-channel imaging processing flow to obtain a reconstructed frequency domain azimuth signal;

[0014] Step 1.5: band-limited filtering the reconstructed frequency domain azimuth signal and inverse Fourier transforming it to the time domain to obtain a time domain azimuth signal. Band-limited filtering the reconstructed frequency domain azimuth signal and inverse Fourier transforming it to the time domain to obtain a time domain azimuth signal.

[0015] Step 1.6: Calculate the azimuth ambiguity of the multi-channel system based on the time domain azimuth signal.

[0016] Preferably, step 1 includes: calculating the azimuth ambiguity of the satellite-borne multi-channel SAR based on simulated echo processing, and superimposing the inter-channel amplitude and phase errors, Doppler center deviation and antenna phase center deviation in the simulation calculation model, while the satellite attitude error, antenna array deployment error and antenna thermal deformation are all converted to the antenna phase center deviation.

[0017] Preferably, the step 1.3 includes: performing spectrum shifting before Fourier transforming the generated time-domain azimuth echo signal, and unifying the processing methods when the total number of channels of the multi-channels is an odd number or an even number.

[0018] Preferably, the step 1.4 includes: using an "inverse filtering method" to perform spectrum reconstruction.

[0019] Preferably, the step 1.5 comprises: before inverse Fourier transforming the reconstructed frequency domain azimuth signal into the time domain, filtering with the Doppler processing bandwidth as a band limit.

[0020] Preferably, the step 1.6 comprises: expanding the integral summation interval when calculating the main lobe energy.

[0021] According to the present invention, a system for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR is provided, comprising the following modules:

[0022] Module M1: Get the azimuth ambiguity under the error condition of spaceborne multi-channel SAR;

[0023] Module M2: According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized, and the index requirements of the spaceborne multi-channel SAR system under the error conditions are obtained through iteration.

[0024] Preferably, the module M1 includes the following modules:

[0025] Module M1.1: Set the number of fuzzy zones to obtain the number of azimuth sampling points;

[0026] Module M1.2: Generate a time domain azimuth echo signal with an ambiguous area under error conditions by simulation according to the azimuth sampling point number;

[0027] Module M1.3: performing spectrum shifting and Fourier transform on the time domain azimuth echo signal to obtain a frequency domain azimuth echo signal;

[0028] Module M1.4: Perform spectrum reconstruction on the frequency domain azimuth echo signal according to the multi-channel imaging processing flow to obtain a reconstructed frequency domain azimuth signal;

[0029] Module M1.5: Band-limited filtering is performed on the reconstructed frequency domain azimuth signal and inverse Fourier transform is performed to the time domain to obtain the time domain azimuth signal;

[0030] Module M1.6: Calculate the azimuth ambiguity of the multi-channel system based on the time domain azimuth signal.

[0031] Preferably, the module M1 includes: calculating the azimuth ambiguity of the satellite-borne multi-channel SAR based on simulated echo processing, and superimposing the inter-channel amplitude and phase errors, Doppler center deviation and antenna phase center deviation in the simulation calculation model, while the satellite attitude error, antenna array deployment error and antenna thermal deformation are all converted to the antenna phase center deviation.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. The present invention calculates the satellite-borne multi-channel azimuth ambiguity based on echo simulation processing, which can superimpose various errors of the satellite-to-ground full link, effectively solving the problem of the lack of accurate error model in the azimuth ambiguity calculation of traditional satellite-borne multi-channel SAR, and has important guiding significance for the optimization design and engineering development of satellite-borne multi-channel SAR systems;

[0034] 2. The calculation logic of the present invention is clear and the calculation model is accurate. The direct calculation model requires complex mathematical deduction, especially under multiple error conditions, the deduction of the mathematical calculation model will become extremely difficult. The present invention is based on simulated echo processing, which is a forward deduction process with clear logic and easy to understand. In addition, no approximation is made in the intermediate processing process, and the simulation calculation results are more accurate.

[0035] 3. The present invention can perform quantitative calculations, which is superior to direct calculation models and has important guiding significance for system optimization and engineering development. The present invention can superimpose various errors of the entire satellite-to-ground link, can quantitatively calculate the azimuth ambiguity index under single error conditions, and can also calculate the azimuth ambiguity index under the combined influence of multiple errors, which has important guiding significance for system optimization and engineering development. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0037] Figure 1 It is a flow chart of the method and system for calculating azimuth ambiguity under the error condition of the spaceborne multi-channel SAR of the present invention;

[0038] Figure 2 is the time domain azimuth echo signal of each channel obtained by simulating the system parameters in Example 1;

[0039] Figure 3 is the frequency domain azimuth signal after the spectrum reconstruction processing in Example 1;

[0040] Figure 4 is the time domain azimuth signal after band-limited filtering in Example 1;

[0041] Figure 5 is the main lobe energy boundary corresponding to k being 4 in step 1.6 of embodiment 1;

[0042] Figure 6 is a multi-channel AASR versus PRF curve calculated by the method of the present invention in Example 1;

[0043] Figure 7 is the time domain azimuth echo signal of each channel obtained by simulating the system parameters and error parameters in Example 2;

[0044] Figure 8is the frequency domain azimuth signal after the spectrum reconstruction processing in Example 2;

[0045] Fig. 9 is the time domain azimuth signal after band-limited filtering in Example 2;

[0046] Fig.10 is the main lobe energy boundary corresponding to k being 4 in step 1.6 of embodiment 2;

[0047] Fig.11 This is a curve of multi-channel AASR changing with PRF under different distributed amplitude and phase error conditions calculated by the present invention in Example 2. DETAILED DESCRIPTION

[0048] The present invention is described in detail below in conjunction with specific embodiments. The following embodiments 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 of ordinary skill in the art, several changes and improvements can also be made without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0049] Embodiment 1 of the present invention discloses a method and system for calculating azimuth ambiguity under satellite-borne multi-channel SAR error conditions, such as Figure 1 As shown, the following steps are included: Step 1: Obtain the azimuth ambiguity under the error condition of the spaceborne multi-channel SAR. Step 1 includes the following steps: Step 1.1: Set the number of fuzzy zones to obtain the number of azimuth sampling points. Set the number of fuzzy zones and calculate the number of azimuth sampling points according to the system working parameters.

[0050] Set the number of sampling points in the azimuth direction corresponding to the Mth fuzzy area when calculating AASR, N a The calculation is done using the following formula:

[0051]

[0052] Where N is the total number of receiving channels, · represents multiplication, round{*} represents rounding to the nearest integer, λ is the wavelength, and R B is the shortest slant distance from the target to the satellite, PRF is the pulse repetition frequency, V r is the satellite speed.

[0053] Step 1.2: Generate a time domain azimuth echo signal with an ambiguous area under error conditions by simulation according to the number of azimuth sampling points. Generate a time domain azimuth echo signal with an ambiguous area under error conditions by simulation.

[0054] Consider the X, Y, and Z coordinate positions as (P Px ,P Py ,P Pz ) point target, at the azimuth time t a, the X, Y, and Z coordinate positions of the satellite are (P Sx ,P Sy ,P Sz ), P Sx Satisfy P Sx =V r t a Considering the amplitude and phase errors of the receiving channel, the azimuth echo signal s of the nth receiving channel is n (t a ; R B ) can be simplified as:

[0055]

[0056] Among them, G t (t a ; R B ) is the satellite antenna transmission pattern, G r,n (t a ; R B ) is the receiving pattern of the nth channel of the satellite antenna, R t (t a ; R B ) is the distance from the satellite antenna to the target when the satellite antenna transmits the signal, R r,n (t a ; R B ) is the distance from the target to the nth receiving channel of the satellite antenna when the satellite antenna receives the signal, and j represents the imaginary unit, that is, exp represents an exponential function with the natural constant e as the base; it is calculated using the following formulas:

[0057]

[0058]

[0059]

[0060]

[0061] In the above formulas:

[0062] t a is the azimuth time, and its value range is

[0063] Δa e,n is the amplitude error of the nth channel, is the phase error of the nth channel;

[0064] Δx e,n , Δy e,n , Δz e,nare the position deviations of the phase center in the x, y, and z directions of the nth receiving channel, respectively. Factors affecting the position deviation of the phase center include satellite attitude error, antenna array deployment error, and antenna thermal deformation.

[0065] Δf dc_t is the Doppler center deviation of the transmitting antenna, Δf dc_r,n is the Doppler center deviation of the nth receiving channel antenna;

[0066] G t is the azimuth transmission pattern, G r,i is the azimuth receiving pattern of the nth receiving channel. Here, the standard sinc pattern is used. The actual measured pattern should be used in engineering research and development.

[0067] R t is the slant distance from the target to the transmitting phase center, R r,i is the slant distance from the target to the receiving phase center of the nth channel;

[0068] D at Indicates the size of the transmitting antenna in azimuth;

[0069] D ar Indicates the size of the receiving antenna in azimuth.

[0070] Step 1.3: Spectrum shifting and Fourier transforming of the time-domain azimuth echo signal. Spectrum shifting is performed before Fourier transforming the generated time-domain azimuth echo signal, unifying the processing methods when the total number of multi-channels is odd and even. Spectrum shifting and Fourier transforming of the generated time-domain azimuth echo signal is performed.

[0071] The time domain azimuth echo signal with ambiguity under the error condition generated by simulation is subjected to Fourier transform (FFT). Considering that the total number of receiving channels N may be an odd number or an even number, the spectrum is shifted before FFT to obtain the frequency domain signal S 1,n (f a ):

[0072] S 1,n (f a )=FFT{s n (t a ; R B )·H shift (t a )} (7)

[0073] Among them, H shift (t a ) is the spectrum shift function, which can be expressed as:

[0074]

[0075] In the above formula, f a is the azimuth frequency, is the spectrum shift amount, and rem(N,2) represents the remainder operation of the number of channels N divided by 2.

[0076] Step 1.4: Perform spectrum reconstruction on the azimuth echo signal according to the multi-channel imaging processing flow to obtain the reconstructed frequency domain azimuth signal. Use the "inverse filtering method" to perform spectrum reconstruction. Perform spectrum reconstruction on the azimuth echo signal according to the multi-channel imaging processing flow.

[0077] The spectrum of the generated azimuth echo signals of each channel is reconstructed. Here, the specific processing method is introduced by taking the "inverse filtering method" as an example: Construct the system transfer function matrix Hf n (f a ), divided into the frequency-independent term Hf 1,n and frequency-dependent term Hf 2,n (f a ) are divided into two parts, as follows:

[0078] Hf n (f a )=Hf 1,n ·Hf 2,n (f a ) (9)

[0079] in,

[0080]

[0081] Where Δx n The distance between the phase center of the nth receiving channel and the phase center of the reference channel. floor(N / 2) means the logarithmic value N / 2 is rounded down. Thus, the spectrum reconstruction result S of each channel can be obtained. 2,n (f a ) is shown in the following formula:

[0082]

[0083] In the above formula, The superscript “*” indicates the conjugation operation; The superscript “-1” in represents the matrix inversion operation.

[0084] Each channel S 2,n Spectrum expansion can be achieved by extracting and reorganizing in sequence according to the frequency points, and N·N a The frequency domain signal with sampling points and equivalent pulse repetition frequency N·PRF is denoted as S 3 (f a ).

[0085] S 3 (fa )=rearrange([S 2,1 (f a ),S 2,2 (f a ),…,S 2,N (f a )]) (13)

[0086] In the above formula, S 2,1 (f a ),S 2,2 (f a ),…,S 2,N (f a ) is formula (12)S 2,n (f a ) traverses n from 1 to N, rearrange(*) means extracting and reorganizing * in frequency order.

[0087] Step 1.5: The reconstructed frequency domain azimuth signal is subjected to band-limited filtering and inverse Fourier transformation to the time domain to obtain a time domain azimuth signal. Before the frequency domain azimuth signal after spectrum reconstruction is inversely Fourier transformed to the time domain, it is filtered with the Doppler processing bandwidth as the band limit. The frequency domain azimuth signal after spectrum reconstruction is subjected to band-limited filtering and inverse Fourier transformation to the time domain.

[0088] Doppler processing bandwidth B p For the band-limited pair S 3 (f a ) to perform spectrum filtering, then perform inverse Fourier transform (IFFT), and then take the absolute value to obtain the time domain amplitude signal s o (f a )for:

[0089]

[0090] In the formula represents a rectangular window with a total length of N·PRF, with the center of the window B p The range is 1, and the rest of the positions are 0; IFFT{*} means inverse Fourier transform of *; |*| means complex modulo operation of *.

[0091] Step 1.6: Calculate the azimuth ambiguity of the multi-channel system based on the time domain azimuth signal. When calculating the main lobe energy, the integral summation interval is expanded to avoid the influence of the main lobe energy leakage on the azimuth ambiguity calculation. Calculate the azimuth ambiguity of the multi-channel system according to the basic definition of the traditional azimuth ambiguity.

[0092] For o (f a ) to calculate the multi-channel AASR. First, the main lobe signal energy E is calculated using the following formulaM :

[0093]

[0094] In the above formula, when calculating the main lobe signal energy, the integration interval of the traditional calculation method is expanded in order to prevent the main lobe signal energy leakage. In the formula, k is the main lobe integration interval expansion factor, For o (f a ) squared, indicating power.

[0095] Integrate the energy of the entire signal and then subtract the main lobe energy from the above formula to get the total energy E in the fuzzy area. S for:

[0096]

[0097] Finally, we get the multi-channel azimuth ambiguity AASR N for

[0098] AASR N =10lg(E S / E M )

[0099] The present invention calculates the azimuth ambiguity of the space-borne multi-channel SAR based on the simulation model. At the same time, the main errors of the satellite-to-ground link such as the inter-channel amplitude and phase error, Doppler center deviation and antenna phase center deviation are superimposed in the simulation calculation model, and the satellite attitude error, antenna array deployment error and antenna thermal deformation are all converted to the antenna phase center deviation.

[0100] Step 2: According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized, and the index requirements of the spaceborne multi-channel SAR system under the error condition are obtained through iteration. According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized and designed, and the design results that meet the index requirements of the whole system under the error condition are finally obtained through iteration.

[0101] The main idea of ​​the present invention is to simulate and generate an azimuth echo signal containing an ambiguous area and superimposed satellite-to-ground link errors according to the system operating parameters, and then reconstruct the azimuth spectrum according to the multi-channel imaging processing flow, and then transform the reconstructed signal into the time domain to calculate the azimuth ambiguity according to the time-frequency correspondence.

[0102] Example 1 Taking the radar system parameters shown in Table 1 below as an example, the method of the present invention is further described in detail, and the simulation calculation results are given when the total number of channels is an odd number and there is no error.

[0103] Table 1 Main simulation parameters

[0104] Parameter name Parameter settings Number of channels (N) 7 <![CDATA[Carrier frequency (f c )]]> 9.6GHz <![CDATA[Azimuthal transmitting antenna size (D at )]]> 3m <![CDATA[Azimuth receiving antenna size (D ar )]]> 1.6m <![CDATA[Satellite velocity (V r )]]> 7560m / s Pulse Repetition Frequency (PRF) 1200Hz~1500Hz <![CDATA[Doppler processing bandwidth (B p )]]> 7600Hz Fuzzy interval counting number (M) 8

[0105] According to step 1.1 of the present invention, taking the PRF as 1300 Hz as an example, the target position is the center of the scene, and its shortest slant distance to the satellite is R B is 7.4445×10 5 , the 8th fuzzy area is obtained, and the number of sampling points in the azimuth direction is calculated to be 40930. Substituting the system working parameters into the echo signal model, we can get Figure 2 The generated time domain azimuth echo signal is subjected to spectrum shifting and Fourier transform, and then spectrum reconstruction is performed according to the multi-channel imaging processing flow to obtain the following: Figure 3 The frequency domain azimuth signal shown in the figure has a dotted line frame, where the shaded area does not consider the Doppler processing bandwidth, and the remaining shaded area considers the Doppler processing bandwidth. The frequency domain azimuth signal after spectrum reconstruction is subjected to band-limited filtering and inverse Fourier transform to the time domain, and the following can be obtained: Figure 4 The time domain azimuth signal shown in FIG. 1 is used to calculate the multi-channel azimuth ambiguity according to the basic definition of the traditional azimuth ambiguity, where k in step 1.6 is 4, and the corresponding main lobe energy boundary is as follows: Figure 5 As shown, the calculated azimuth ambiguity result is -22.22dB.

[0106] Repeating the above steps in the PRF range of 1200Hz to 1500Hz can calculate the azimuth ambiguity curve of the satellite-borne seven-channel SAR as follows: Figure 6 shown.

[0107] Embodiment 2 of the present invention further discloses a method and system for calculating azimuth ambiguity under satellite-borne multi-channel SAR error conditions, which is different from Embodiment 1 in that:

[0108] Example 2 Taking the radar system parameters shown in Table 2 below as an example, the method of the present invention is further described in detail, and the calculation results are given when the total number of channels is an even number and the maximum amplitude and phase error between channels is 0.5dB / 15° (various error distributions, see Table 3).

[0109] Table 2 Main simulation parameters

[0110] Parameter name Parameter settings Number of channels (N) 4 <![CDATA[Carrier frequency (f c )]]> 9.6GHz <![CDATA[Azimuthal transmitting antenna size (D at )]]> 4m <![CDATA[Azimuth receiving antenna size (D ar )]]> 3m <![CDATA[Satellite velocity (V r )]]> 7560m / s Pulse Repetition Frequency (PRF) 1200Hz~1500Hz <![CDATA[Doppler processing bandwidth (B p )]]> 4000Hz Fuzzy interval counting number (M) 8

[0111] Table 3 Inter-channel amplitude and phase error simulation settings

[0112]

[0113] According to step 1.1 of the present invention, taking the PRF as 1300 Hz as an example, the target position is the center of the scene, and its shortest slant distance to the satellite is R B is 7.4445×10 5, get the 8th fuzzy area, and calculate the number of azimuth sampling points to be 23388. Substituting the system operating parameters and error parameters into the echo signal model, the time domain azimuth echo signal of each channel can be obtained, as shown in Figure 7 As shown in the figure, the time domain azimuth echo signals of each channel under the linear distribution amplitude and phase error are given. The generated time domain azimuth echo signal is subjected to spectrum shifting and Fourier transform, and then the spectrum is reconstructed according to the multi-channel imaging processing flow, and the following can be obtained: Figure 8 The frequency domain azimuth signal shown in the figure has a dotted line frame, where the shaded area does not consider the Doppler processing bandwidth, and the remaining shaded area considers the Doppler processing bandwidth. The frequency domain azimuth signal after spectrum reconstruction is subjected to band-limited filtering and inverse Fourier transform to the time domain, and the following can be obtained: Fig. 9 The time domain azimuth signal shown in FIG. 1 is used to calculate the multi-channel azimuth ambiguity according to the basic definition of the traditional azimuth ambiguity, where k in step 1.6 is 4, and the corresponding main lobe energy boundary is as follows: Fig.10 As shown, the calculated azimuth ambiguity result is -25.39dB.

[0114] The PRF repeats the above steps in the range of 1200Hz to 1500Hz according to the different distributions of inter-channel amplitude and phase errors, and the azimuth ambiguity curves under the different distributions of inter-channel amplitude and phase errors of the satellite-borne four-channel SAR can be calculated as follows: Fig.11 shown.

[0115] The present invention relates to the field of radar technology and can be used for azimuth ambiguity calculation in the development of satellite-borne multi-channel SAR engineering. The present invention can superimpose various errors of the satellite-to-ground full link, effectively solving the problem that there is no accurate error model for azimuth ambiguity calculation of satellite-borne multi-channel SAR at home and abroad.

[0116] Those skilled in the art know that, in addition to realizing the system and its various devices, modules, and units provided by the present invention in a purely computer-readable program code, it is entirely possible to realize the same functions 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 as a hardware component, and the devices, modules, and units included therein for realizing various functions can also be regarded as structures within the hardware component; the devices, modules, and units for realizing various functions can also be regarded as both software modules for realizing the method and structures within the hardware component.

[0117] The above describes the specific embodiments of the present invention. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. In the absence of conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. A method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR, characterized in that: The steps include: Step 1: Obtain the azimuth ambiguity under the error condition of the spaceborne multi-channel SAR; Step 2: According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized, and the index requirements of the spaceborne multi-channel SAR system under the error condition are obtained through iteration; The step 1 comprises the following steps: Step 1.1: Set the number of fuzzy zones to obtain the number of azimuth sampling points; Step 1.2: Generate a time domain azimuth echo signal with an ambiguous area under an error condition by simulation according to the azimuth sampling point number; Step 1.3: performing spectrum shifting and Fourier transform on the time domain azimuth echo signal to obtain a frequency domain azimuth echo signal; Step 1.4: Perform spectrum reconstruction processing on the frequency domain azimuth echo signal according to the multi-channel imaging processing flow to obtain a reconstructed frequency domain azimuth signal; Step 1.5: Perform band-limited filtering on the reconstructed frequency domain azimuth signal and inverse Fourier transform it to the time domain to obtain the time domain azimuth signal; Step 1.6: Calculate the azimuth ambiguity of the multi-channel system based on the time domain azimuth signal.

2. The method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR according to claim 1, characterized in that: The step 1 comprises: calculating the azimuth ambiguity of the satellite-borne multi-channel SAR based on simulated echo processing, and superimposing the inter-channel amplitude and phase errors, Doppler center deviation and antenna phase center deviation in the simulation calculation model, while the satellite attitude error, antenna array deployment error and antenna thermal deformation are all converted to the antenna phase center deviation.

3. The method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR according to claim 1, characterized in that: The step 1.3 includes: performing spectrum shifting before Fourier transforming the generated time-domain azimuth echo signal, and unifying the processing method when the total number of channels of the multi-channels is an odd number or an even number.

4. The method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR according to claim 1, characterized in that: The step 1.4 includes: using the "inverse filtering method" to reconstruct the spectrum.

5. The method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR according to claim 1, characterized in that: The step 1.5 comprises: before inverse Fourier transforming the reconstructed frequency domain azimuth signal into the time domain, filtering with the Doppler processing bandwidth as the band limit.

6. The method for calculating azimuth ambiguity under error conditions of a spaceborne multi-channel SAR according to claim 1, characterized in that: The step 1.6 includes: expanding the integral summation interval when calculating the main lobe energy.

7. A system for calculating azimuth ambiguity under satellite-borne multi-channel SAR error conditions, characterized in that , the azimuth ambiguity calculation method under the error condition of the spaceborne multi-channel SAR described in any one of claims 1-6 includes the following modules: Module M1: Get the azimuth ambiguity under the error condition of spaceborne multi-channel SAR; Module M2: According to the azimuth ambiguity, the spaceborne multi-channel SAR system is optimized, and the index requirements of the spaceborne multi-channel SAR system under the error conditions are obtained through iteration.

8. The azimuth ambiguity calculation system under the error condition of the spaceborne multi-channel SAR according to claim 7, characterized in that: The module M1 includes the following modules: Module M1.1: Set the number of fuzzy zones to obtain the number of azimuth sampling points; Module M1.2: Generate a time domain azimuth echo signal with an ambiguous area under error conditions by simulation according to the azimuth sampling point number; Module M1.3: performing spectrum shifting and Fourier transform on the time domain azimuth echo signal to obtain a frequency domain azimuth echo signal; Module M1.4: Perform spectrum reconstruction on the frequency domain azimuth echo signal according to the multi-channel imaging processing flow to obtain a reconstructed frequency domain azimuth signal; Module M1.5: Band-limited filtering is performed on the reconstructed frequency domain azimuth signal and inverse Fourier transform is performed to the time domain to obtain the time domain azimuth signal; Module M1.6: Calculate the azimuth ambiguity of the multi-channel system based on the time domain azimuth signal.

9. The azimuth ambiguity calculation system under the error condition of the spaceborne multi-channel SAR according to claim 7, characterized in that: The module M1 includes: calculating the azimuth ambiguity of the satellite-borne multi-channel SAR based on simulated echo processing, and superimposing the inter-channel amplitude and phase errors, Doppler center deviation and antenna phase center deviation in the simulation calculation model, while the satellite attitude error, antenna array deployment error and antenna thermal deformation are all converted to the antenna phase center deviation.

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