A method for azimuth ambiguity suppression of spaceborne SAR with spatial non-uniform sampling

Abstract

The present invention discloses a method for suppressing azimuth ambiguity of a space-borne SAR with non-uniform spatial sampling, and relates to the field of radar technology, including: step 1, compensating for the phase difference between two stations of each channel echo; step 2, calculating the equivalent azimuth sampling position of each channel at each pulse emission moment; step 3, sorting the equivalent azimuth sampling positions of all channels and their corresponding echoes after compensating for the phase difference between two stations in ascending order; step 4, calculating the reconstructed echo from the sorted equivalent azimuth sampling positions and their corresponding echoes after compensating for the phase difference between two stations using an adaptive weight-conjugate gradient-Toeplitz matrix (ACT) algorithm. The present invention does not require that the relative distance between each channel remain unchanged, and greatly expands the scope of application of azimuth multi-channel SAR echo reconstruction.

Description

Technical Field

[0001] The invention belongs to the field of radar technology, and in particular to a method for suppressing azimuth ambiguity of a space-borne SAR with spatial non-uniform sampling. Background Art

[0002] Synthetic Aperture Radar (SAR) is an active imaging radar with all-day and all-weather ground observation capabilities. SAR transmits electromagnetic waves to the target area multiple times from different angles and receives echo signals, and obtains a two-dimensional image of the target area through synthetic aperture imaging algorithm processing. There is a mutually restrictive relationship between the pulse repetition frequency (PRF) and range width of the SAR system. In recent years, azimuth multi-channel technology has been proposed to achieve high-resolution and wide-band SAR. Its working method is that after a pulse is transmitted, multiple receiving channels at different spatial positions simultaneously receive echoes. Azimuth multi-channel technology can achieve a multiple reduction in the PRF required for the same azimuth resolution, and is currently an important technology for achieving high-resolution and wide-band SAR.

[0003] When performing azimuth multi-channel SAR imaging, the multi-channel echoes need to be reconstructed into equivalent single-channel echoes. The existing reconstruction method was proposed by Krieger et al. of German Aerospace in 2004 and is implemented through a filter bank. This method is based on the principle of periodic non-uniform sampling and requires that the relative positions of the transmitting channel and each receiving channel remain unchanged. For a single-platform system, this condition is easy to meet, but for a distributed system, the relative positions between the channels are easily affected by the relative motion between the platforms and change, which deteriorates the effect of the filter bank reconstruction method and cannot meet the imaging requirements. Summary of the invention

[0004] In order to solve the above technical problems, the present invention provides a method for azimuth ambiguity suppression of space-borne SAR with spatial non-uniform sampling. The method is based on the principle of complete non-uniform sampling, and reconstructs an equivalent single-channel echo from a multi-channel echo according to the relative position between the channels at each pulse emission moment. Compared with the existing reconstruction method, the proposed method does not require the relative distance between the channels to remain unchanged, which greatly expands the scope of application of azimuth multi-channel SAR echo reconstruction.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] A method for suppressing azimuth ambiguity of a space-borne SAR with spatial non-uniform sampling comprises the following steps:

[0007] Step 1, compensating for the phase difference between the transmitting and receiving stations of the echo of each channel;

[0008] Step 2, calculating the equivalent azimuth sampling position of each channel at each pulse emission moment;

[0009] Step 3, sorting the equivalent azimuth sampling positions of all channels and their corresponding echoes after compensating for the phase difference between the transmitting and receiving stations in ascending order;

[0010] Step 4: Calculate the reconstructed echo using the adaptive weight-conjugate gradient-Toeplitz matrix (ACT) algorithm combined with the sorting result of step 3.

[0011] The beneficial effects of the present invention are:

[0012] The present invention does not require the relative distance between channels to remain unchanged. It can effectively complete echo reconstruction in the case of relative motion between channels. Compared with the existing filter bank reconstruction method, it can significantly suppress the blurred targets that appear after azimuth compression, and the blurred target energy is reduced by 30dB, which greatly expands the scope of application of azimuth multi-channel SAR echo reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 This is a flow chart of a method for suppressing azimuth ambiguity of a space-borne SAR with spatial non-uniform sampling according to the present invention;

[0014] Figure 2 (a) shows the spectrum of the echo after reconstruction using the traditional filter bank method;

[0015] FIG2( b ) is the spectrum of the echo after reconstruction based on the method of the present invention;

[0016] Figure 3 (a) shows the result of echo azimuth compression after reconstruction using the traditional filter bank method;

[0017] FIG3( b ) is the result of echo azimuth compression after reconstruction based on the method of the present invention. DETAILED DESCRIPTION

[0018] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the protection scope of the present invention.

[0019] According to an embodiment of the present invention, Figure 1 As shown, a method for suppressing azimuth ambiguity of a space-borne SAR with spatial non-uniform sampling according to the present invention comprises the following steps:

[0020] Step 1: Compensate for the phase difference between the transmitting and receiving stations of each channel echo:

[0021] Assume that the operating carrier wavelength of the azimuth multi-channel SAR system is The SAR system includes 1 transmitting channel and M receiving channels, transmitting N pulses in total. Each time a pulse is transmitted from the transmitting channel, it is received by the M receiving channels respectively. The pulse repetition frequency is recorded as , the nominal moving speed is v. There is only a position offset between each receiving channel and the transmitting channel in the azimuth direction. The emission time of the pulse, the azimuth position of the emission channel is recorded as , at this moment The relative position of the receiving channel and the transmitting channel in azimuth is recorded as The received multi-channel echo is recorded as , where r is the sampling point in the range direction, and the reference slant distance of the imaging scene is ; then the multi-channel echo after compensating the phase difference between the transmitting and receiving stations It is expressed as:

[0022] (1)

[0023] Among them, exp represents the natural exponential operation, represents an imaginary number, Represents pi.

[0024] Step 2: Calculate the equivalent azimuth sampling position of each channel at each pulse emission moment:

[0025] For the emission time of the i-th pulse and the k-th receiving channel, the corresponding equivalent azimuth sampling position is It is expressed as:

[0026] (2)

[0027] Step 3: Sort the equivalent azimuth sampling positions of all channels and their corresponding echoes after compensating for the phase difference between the transmitting and receiving stations in ascending order:

[0028] Sort the transmission time of N pulses and all equivalent azimuth sampling positions corresponding to M receiving channels in ascending order. The sorted equivalent azimuth sampling position set It is expressed as:

[0029] (3)

[0030] The corresponding multi-channel echo after compensating the phase difference between the transmitting and receiving stations is expressed in ascending order as follows:

[0031] (4).

[0032] Step 4: Use the adaptive weight-conjugate gradient-Toeplitz matrix (ACT) algorithm to calculate the reconstructed echo from the sorted equivalent azimuth sampling positions and their corresponding echoes after compensating the phase difference between the transmitting and receiving stations. The ACT algorithm was proposed by Feichtinger et al. in 1995. It is an efficient numerical solution algorithm for completely non-uniform sampling, which can calculate a uniformly sampled signal from a completely non-uniformly sampled finite bandwidth signal. The process for calculating the reconstructed echo is as follows:

[0033] The sorted equivalent azimuths are directed to the sampling positions Normalize so that , expressed as:

[0034] (5)

[0035] In the formula, Represents the normalized and sorted equivalent azimuth sampling position ,set up , , then the adaptive weight is calculated as:

[0036] (6)

[0037] Required Toeplitz matrix for The square matrix, the element in the mth row and nth column of the square matrix is ​​expressed as:

[0038] (7)

[0039] For each range sampling point r, iteratively calculate the reconstructed echo, and set the first, second, and third iteration vectors Both The initial values ​​of the first, second, and third iteration vectors are set to , , the third iteration vector The mth element of is:

[0040] (8)

[0041] For the qth iteration, each vector is updated as:

[0042] (9)

[0043] The superscript T represents the transpose of a vector or matrix. Let the number of iterations be .at this time is the spectrum of the reconstructed echo. It is expressed as:

[0044] (10)

[0045] Among them, IFFT is inverse fast Fourier transform.

[0046] Example

[0047] In this embodiment, the feasibility of the proposed method is verified by simulating the Doppler echo of a single point target of a two-channel SAR system in azimuth of two platforms. The simulation parameters are shown in Table 1.

[0048] Table 1

[0049] ,

[0050] The echo simulation process is as follows; the working carrier wavelength of the azimuth multi-channel SAR system is The whole system consists of 1 transmitting channel and M = 2 receiving channels. The antenna phase center of the transmitting channel coincides with that of the first receiving channel, and both are located on the first platform. The second receiving channel is located on the second platform, and the azimuth antenna lengths of the two platforms are , a total of N = 2030 pulses are transmitted, and the pulse repetition frequency is The moving speeds of the first and second platforms are and , the nominal moving speed of the system is The average distances between the two receiving channels and the transmitting channel are and For the At the moment of pulse emission, the azimuth position of the emission channel is , at this moment The relative position of the receiving channel and the transmitting channel in azimuth The reference slant range of the imaging point target is , the received Doppler echo after channel error correction, phase synchronization and other preprocessing is:

[0051] (11)

[0052] Where rect is the rectangular window function.

[0053] FIG2 (a) and FIG2 (b) respectively show the frequency spectrum of the echo reconstructed by the traditional filter bank method and the method of the present invention. It can be seen that the frequency spectrum of the echo reconstructed by the method of the present invention is significantly better than the result of the traditional filter bank method.

[0054] To verify the reconstruction effect, the reconstructed echo Perform azimuth compression. The echo after azimuth compression is expressed as:

[0055] (12)

[0056] in, is the azimuth frequency, FFT is the fast Fourier transform, and IFFT is the fast inverse Fourier transform. Figure 3 (a) and Figure 3 (b) respectively show the results of echo azimuth compression after reconstruction by the traditional filter bank method and the method of the present invention. It can be seen that the false target energy is reduced by 30dB by the method of the present invention.

[0057] The specific embodiments described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for azimuth ambiguity suppression of spaceborne SAR with spatial non-uniform sampling, characterized in that: The steps include: Step 1, compensating for the phase difference between the transmitting and receiving stations of the echo of each channel; Step 2, calculating the equivalent azimuth sampling position of each channel at each pulse emission moment; Step 3, sorting the equivalent azimuth sampling positions of all channels and their corresponding echoes after compensating for the phase difference between the transmitting and receiving stations in ascending order; Step 4: Calculate the reconstructed echo using the adaptive weight-conjugate gradient-Toeplitz matrix algorithm combined with the sorting result of step 3, including: The sorted equivalent azimuth sampling position set Normalize so that , expressed as: (5) In the formula, Represents the normalized and sorted equivalent azimuth sampling position set , l represents the index of the equivalent azimuth sampling position after sorting, M represents the number of receiving channels, N represents the number of pulse transmissions, and v represents the nominal moving speed. represents the pulse repetition frequency, , , then the adaptive weight is calculated as: （6） Required Toeplitz matrix for The element in the mth row and nth column of the square matrix is ​​expressed as : (7) For each range sampling point r, iteratively calculate the reconstructed echo, and set the first, second, and third iteration vectors Both , where q is the number of iterations, and the initial values ​​of the first, second, and third iteration vectors are set to , , the third iteration vector The mth element of is: (8) For the qth iteration, each iteration vector is updated as: (9) The superscript T represents the transpose of a vector or matrix. Let Q be the number of iterations. is the spectrum of the reconstructed echo. It is expressed as: (10) Among them, IFFT is inverse fast Fourier transform.

2. The method for azimuth ambiguity suppression of space-borne SAR with spatial non-uniform sampling according to claim 1, characterized in that: The step 1 comprises: Assume that the operating carrier wavelength of the azimuth multi-channel SAR system is The SAR system includes 1 transmitting channel and M receiving channels, transmitting N pulses in total. Each time a pulse is transmitted from the transmitting channel, it is received by the M receiving channels respectively. The pulse repetition frequency is recorded as , the nominal moving speed is v; for the The emission time of the pulse, the azimuth position of the emission channel is recorded as , at this moment The relative position of the receiving channel and the transmitting channel in azimuth is recorded as The received multi-channel echo is recorded as , where r is the sampling point in the range direction, and the reference slant distance of the imaging scene is ; The multi-channel echo after compensating the phase difference between the transmitting and receiving stations is It is expressed as: (1) Among them, exp represents the natural exponential operation, represents an imaginary number, Represents pi.

3. The method for azimuth ambiguity suppression of space-borne SAR with spatial non-uniform sampling according to claim 1, characterized in that: The step 2 comprises: The transmission time of the i-th pulse and the equivalent azimuth sampling position corresponding to the k-th receiving channel It is expressed as: (2)， In the formula, for the The emission time of the pulse, the azimuth position of the emission channel is recorded as , at this moment The relative position of the receiving channel and the transmitting channel in azimuth is recorded as .

4. The method for suppressing azimuth ambiguity of a space-borne SAR using spatial non-uniform sampling according to claim 1, characterized in that: The step 3 comprises: Sort the transmission time of N pulses and all equivalent azimuth sampling positions corresponding to M receiving channels in ascending order. The sorted equivalent azimuth sampling position set It is expressed as: (3) In the formula, l represents the sorted equivalent azimuth sampling position index; The corresponding multi-channel echo after compensating the phase difference between the transmitting and receiving stations is expressed as follows after being sorted in ascending order: (4)， It represents the multi-channel echo after compensating the phase difference between the transmitting and receiving stations. The emission time of the pulse, the azimuth position of the emission channel is recorded as , at this moment The relative position of the receiving channel and the transmitting channel in azimuth is recorded as , r is the distance to the sampling point, It represents the transmission time of the i-th pulse and the equivalent azimuth sampling position corresponding to the k-th receiving channel. The left arrow ← indicates that the former equation is a necessary condition for the latter equation, that is, if the latter equation holds, the former equation holds.

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