Satellite-borne radar sea surface target signal pulse accumulation and clutter suppression method

Abstract

The invention discloses a spaceborne radar sea surface target signal pulse accumulation and clutter suppression method, which comprises the following steps of: reconstructing an azimuth time variable by utilizing second-order keystone transformation to obtain an echo signal after distance correction, extracting an azimuth signal of the same distance unit from the echo signal after distance correction through a de-chirp function, and processing the azimuth signal to obtain a clutter suppression signal; therefore, de-chirping of the azimuth signal is realized; intra-frame coherent inter-frame non-coherent hybrid accumulation processing is carried out on an intra-frame signal of a decomposed frequency domain to obtain an echo signal containing a target signal and clutter, and the problems of span distance and Doppler unit in long-time accumulation of a moving target are optimized; the method comprises the following steps: performing inverse Fourier transform on an echo signal containing a target signal and clutter to obtain a singular value matrix after clutter suppression, and performing slow time Fourier transform on a reconstructed echo matrix to obtain an accumulation result after clutter suppression. The problem that the moving target detection performance of an existing spaceborne radar is insufficient under the influence of clutters existing in echo signals is solved.

Description

Technical Field

[0001] The present invention belongs to the technical field of radar, and particularly relates to a method for pulse accumulation and clutter suppression of spaceborne radar sea surface target signals. Background Art

[0002] When a spaceborne radar detects sea surface targets, it usually faces the challenge of complex and variable echo signals. Due to the high-speed movement of the spaceborne radar relative to ground targets, its echo signals are easily affected by Doppler frequency shift, resulting in target echo signals spanning multiple range cells and Doppler cells, increasing the complexity of signal processing. In addition, the background clutter energy in the sea surface environment is strong, causing serious interference to the detection of targets.

[0003] After retrieval, it is found that the Chinese invention "A long-time accumulation detection method for bistatic radar" with the publication number "CN119224758A" discloses a long-time accumulation detection method based on bistatic radar. By improving the interpolation strategy in range dimension FFT processing, this method significantly reduces the influence of quantization error on the energy accumulation accuracy, and further improves the energy concentration degree and target detection performance during long-time accumulation. This patent also proposes an effective range migration correction algorithm, enabling the radar to more accurately correct the movement trajectory of the target, thereby realizing the efficient accumulation processing of pulse echo signals. However, this technology does not fully consider the interference problem of clutter background on signal coherent accumulation during the process of target detection. The clutter background will significantly affect the separation effect of target signals, and thus have an adverse impact on the detection performance of the radar. Therefore, when this method is actually applied to complex environments, its clutter suppression ability still has limitations.

[0004] After retrieval, it is found that the Chinese invention "A sea surface weak target detection method, system and storage medium based on sea clutter suppression" with the publication number "CN119247312A" discloses a sea surface weak target detection method, system and storage medium based on sea clutter suppression. The method performs wavelet transform on the target echo signals of the radar, changes the time and frequency resolution by scale stretching to obtain time-frequency domain components at different scales, uses the correlation between sea clutter in adjacent range cells of the sea surface and between multiple observation values of the echo in the same range resolution cell, estimates the clutter of the to-be-detected range cell by using the clutter of adjacent range cells, constructs a Hankel matrix for the echo signals and performs singular value decomposition, and then according to the characteristic that the sea clutter energy is greater than the signal energy in the same Chirp signal, eliminates the large singular values corresponding to the sea clutter to obtain a new Hankel matrix, performs echo signal reconstruction, and detects sea surface targets. This method mainly focuses on suppressing sea clutter and does not involve the field of long-time target accumulation, and does not consider the application of singular value decomposition and signal reconstruction during long-time accumulation. Summary of the Invention

[0005] To solve the above problems existing in the prior art, the present invention provides a method for pulse accumulation of sea surface target signals and clutter suppression in spaceborne radar. The technical problems to be solved by the present invention are realized through the following technical solutions:

[0006] In a first aspect, the present invention provides a method for pulse accumulation of sea surface target signals and clutter suppression in spaceborne radar, the method comprising:

[0007] Based on the range history of the target signal, using a second-order Keystone transform to reconstruct the azimuth time variable, and obtaining the range-corrected echo signal;

[0008] Extracting the azimuth signals of the same range cell from the range-corrected echo signal; obtaining the de-chirped azimuth signals according to the azimuth signals of the same range cell and the corresponding de-chirping function;

[0009] Dividing the de-chirped azimuth signals into N frames along the azimuth direction to obtain the intra-frame signals corresponding to each frame; performing azimuth Fourier transform processing on the intra-frame signals corresponding to each frame to obtain the intra-frame signals in the frequency domain; performing intra-frame coherent and inter-frame non-coherent hybrid accumulation processing on the intra-frame signals in the frequency domain to obtain the accumulated echo signal of the target signal;

[0010] Based on the accumulated echo signal of the target signal, obtaining the total echo signal; constructing a Hankel matrix according to the total echo signal; performing singular value decomposition on the Hankel matrix to obtain the singular value matrix after clutter suppression; obtaining the reconstructed echo matrix according to the singular value matrix after clutter suppression; performing slow-time Fourier transform on the reconstructed echo matrix to obtain the accumulated result after clutter suppression.

[0011] In an embodiment of the present invention, based on the range history of the target signal, using a second-order Keystone transform to reconstruct the azimuth time variable, and obtaining the range-corrected echo signal, includes:

[0012] According to the range history of the target signal and the wavelength corresponding to the carrier frequency, obtaining the Doppler phase caused by the range history of the target signal, and obtaining the target instantaneous Doppler frequency according to the Doppler phase;

[0013] Based on the target instantaneous Doppler frequency, identifying the echo signal corresponding to the target signal after range Fourier transform as the echo signal in the frequency domain; wherein,

[0014] The expression of the echo signal in the frequency domain is as follows:

[0015]

[0016] f dc represents the Doppler centroid, f dr represents the Doppler frequency modulation rate, fd3 represents the third - order Doppler, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η′ represents the azimuth time, T a represents the pulse width, p(f τ ) represents the frequency - domain signal after Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, f τ represents the range - direction frequency variable, f υ represents the carrier frequency of the radar signal, c represents the speed of light, R 0 represents the range history at the initial moment;

[0017] Reconstruct the azimuth time variable by using the positive second - order keystone transform;

[0018] Obtain the range - corrected echo signal based on the echo signal in the frequency domain and the reconstructed azimuth time variable.

[0019] In an embodiment of the present invention, obtaining the range - corrected echo signal based on the echo signal in the frequency domain and the reconstructed azimuth time variable includes:

[0020] According to the reconstructed azimuth time variable, use the positive and negative second - order keystone transforms to remove the coupling between range frequency and azimuth time in the echo signal in the frequency domain, and obtain the range - corrected echo signal; where,

[0021] The expression of the range - corrected echo signal is as follows:

[0022]

[0023] σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T a represents the pulse width, p(f τ ) represents the frequency - domain signal after Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, f τ represents the range - direction frequency variable, f υ represents the carrier frequency of the radar signal, c represents the speed of light, f dr represents the Doppler frequency modulation rate, R 0 represents the range history at the initial moment.

[0024] In an embodiment of the present invention, the expression of the azimuth signal of the same range cell is as follows:

[0025]

[0026] where, σ ηdenotes the complex scattering coefficient, rect() denotes the rectangular window function, η denotes the reconstructed azimuth time variable, T a denotes the pulse width, exp() denotes the exponential function with base e, j denotes the imaginary unit, f υ denotes the carrier frequency of the radar signal, c denotes the speed of light, f dr denotes the Doppler frequency modulation rate, R 0 denotes the range history at the initial time.

[0027] In an embodiment of the present invention, according to the azimuth signal of the same range cell and the corresponding de-chirp function, the de-chirped azimuth signal is obtained, including:

[0028] Construct a de-chirp function according to the reconstructed azimuth time variable;

[0029] Multiply the azimuth signal of the same range cell by the de-chirp function to obtain the de-chirped azimuth signal.

[0030] In an embodiment of the present invention, the expressions of the intra-frame signals corresponding to each frame are as follows:

[0031]

[0032] wherein, σ η denotes the complex scattering coefficient, rect() denotes the rectangular window function, η denotes the reconstructed azimuth time variable, exp() denotes the exponential function with base e, j denotes the imaginary unit, f υ denotes the carrier frequency of the radar signal, c denotes the speed of light, f dr denotes the Doppler frequency modulation rate, R 0 denotes the range history at the initial time, T CPI denotes the duration of each frame, denotes the new Doppler frequency modulation rate, which is determined by the coordinate positions and relative motion speeds of the target signal and the transceiver platform, n = -(N - 1) / 2,..., (N - 1) / 2.

[0033] In an embodiment of the present invention, the expressions of the intra-frame signals in the frequency domain are as follows:

[0034]

[0035] wherein, σ η denotes the complex scattering coefficient, rect() denotes the rectangular window function, η denotes the reconstructed azimuth time variable, T CPI denotes the duration of each frame, denotes the new Doppler frequency modulation rate, which is determined by the coordinate positions and relative motion speeds of the target signal and the transceiver platform, exp() denotes the exponential function with base e, j denotes the imaginary unit, f υrepresents the carrier frequency of the radar signal, c represents the speed of light, f dr represents the Doppler modulation frequency, R 0 represents the distance history at the initial moment, || represents the modulo value, f η represents the Doppler frequency, B represents the in-frame bandwidth,

[0036] In one embodiment of the present invention, the in-frame coherent and inter-frame non-coherent hybrid accumulation processing is performed on the in-frame signal in the frequency domain to obtain the accumulated echo signal of the target signal, including:

[0037] Remove the Doppler walk generated by the second-order phase term in the in-frame signal in the frequency domain to obtain the optimal in-frame accumulation effect;

[0038] Based on the optimal in-frame accumulation effect, perform non-coherent accumulation on the in-frame signals in the frequency domain corresponding to all frames to obtain the accumulated echo signal of the target signal.

[0039] In one embodiment of the present invention, perform singular value decomposition on the Hankel matrix to obtain the singular value matrix after clutter suppression, including:

[0040] Perform singular value decomposition on the Hankel matrix based on the left and right singular value unitary matrices to obtain the singular value diagonal matrix;

[0041] Calculate the difference between adjacent singular values in the singular value diagonal matrix, determine the points where the difference change exceeds the preset threshold, and set the singular values after these points to zero to obtain the singular value matrix after clutter suppression.

[0042] In one embodiment of the present invention, the expression for reconstructing the echo matrix is as follows:

[0043] s′ H = U s Σ s V s H ;

[0044] wherein, s′ H represents the reconstructed echo matrix, U s represents the new left singular value matrix, V s represents the new right singular value matrix, V s H represents the transpose of the new right singular value matrix, Σ s represents the singular value matrix after clutter suppression.

[0045] Advantages of the present invention:

[0046] In the solution provided by the present invention, the azimuth time variable is reconstructed by using the second-order Keystone transform to obtain the echo signal after range correction. The de-chirp function is used to process the azimuth signal extracted from the echo signal after range correction for the same range cell to achieve de-chirping of the azimuth signal. By performing intra-frame coherent and inter-frame non-coherent hybrid accumulation processing on the intra-frame signals in the decomposed frequency domain, the echo signal containing the target signal and clutter is obtained, optimizing the problems of cross-range and Doppler cell in the long-time accumulation of moving targets. Based on the inverse Fourier transform of the echo signal containing the target signal and clutter, the singular value matrix after clutter suppression is obtained, and the slow-time Fourier transform is performed on the reconstructed echo matrix to obtain the accumulation result after clutter suppression, solving the problem of insufficient moving target detection performance of existing spaceborne radars due to the influence of clutter in the echo signal. This enables the present invention to have the capabilities of cross-range cell correction, cross-Doppler cell correction, long-time energy accumulation, and clutter suppression in engineering practice, improving the accuracy of moving target detection in the clutter background of spaceborne radars. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 FIG. is a schematic diagram of the steps of a method for pulse accumulation and clutter suppression of sea surface target signals of a spaceborne radar provided by an embodiment of the present invention;

[0048] Figure 2 FIG. is an effect diagram of long-time pulse accumulation of moving targets in a clutter background for a method for pulse accumulation and clutter suppression of sea surface target signals of a spaceborne radar provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The following further describes the present invention in detail with reference to specific embodiments, but the embodiments of the present invention are not limited thereto.

[0050] An embodiment of the present invention provides a method for pulse accumulation and clutter suppression of sea surface target signals of a spaceborne radar, as Figure 1 shown, which may include:

[0051] S1. Based on the range history of the target signal, the azimuth time variable is reconstructed by using the second-order Keystone transform to obtain the echo signal after range correction.

[0052] For S1, it may include:

[0053] S11. According to the range history of the target signal and the wavelength corresponding to the carrier frequency, the Doppler phase caused by the range history of the target signal is obtained, and the instantaneous Doppler frequency of the target is obtained according to the Doppler phase.

[0054] Among them, the expression of the Doppler phase caused by the range history of the target signal is as follows:

[0055]

[0056] In the formula, η′ represents the azimuth time, represents the Doppler phase, R(η′) represents the distance history of the target signal, and λ represents the wavelength corresponding to the carrier frequency.

[0057] The expression of the target instantaneous Doppler frequency is as follows:

[0058]

[0059] In the formula, f d (η′) represents the instantaneous Doppler frequency of the target, represents the derivative of the Doppler phase, and R′(η′) represents the derivative of the range history of the target signal.

[0060] S12, based on the instantaneous Doppler frequency of the target, confirm the echo signal corresponding to the target signal after the range is Fourier transformed as the echo signal in the frequency domain.

[0061] The expression of the echo signal in the frequency domain is as follows:

[0062]

[0063] f dc represents the Doppler centroid, f dr represents the Doppler modulation frequency, f d3 represents the third-order Doppler, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η′ represents the azimuth time, T a Indicates the pulse width, p(f τ ) represents the frequency domain signal after the Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f τ represents the distance frequency variable, f υ represents the radar signal carrier frequency, c represents the speed of light, R 0 Represents the distance history from the initial moment.

[0064] Specifically, the expression of Doppler centroid is as follows:

[0065]

[0066] In the formula, f dc represents the Doppler centroid, f d (η′)| η′＝0 represents the Doppler frequency at the initial moment, k 1 Indicates the first parameter of the preset.

[0067] The expression of Doppler modulation frequency is as follows:

[0068]

[0069] In the formula, f dr represents the Doppler modulation frequency, and f′ d (η)| η＝0 represents the derivative of the Doppler frequency at the initial moment, and k 2 represents a preset second parameter.

[0070] The expression of the third-order Doppler is as follows:

[0071]

[0072] In the formula, f d3 represents the third-order Doppler, and f″ d (η)| η＝0 represents the second derivative of the Doppler frequency at the initial moment, and k 3 represents a preset third parameter.

[0073] The Doppler centroid, Doppler modulation frequency, and third-order Doppler are confirmed according to the target instantaneous Doppler frequency, so as to obtain the echo signal in the frequency domain.

[0074] S13. Use the positive second-order keystone transform to reconstruct the azimuth time variable; where

[0075] The expression of the reconstructed azimuth time variable is as follows:

[0076]

[0077] In the formula, η represents the reconstructed azimuth time variable, f ν represents the radar signal carrier frequency, and f τ represents the range frequency variable, and η m represents a preset new reconstructed azimuth time. η m can be set according to specific requirements.

[0078] S14. Based on the echo signal in the frequency domain and the reconstructed azimuth time variable, obtain the range-corrected echo signal, which may include:

[0079] According to the reconstructed azimuth time variable, use the positive and negative second-order keystone transforms to remove the coupling of the range frequency and azimuth time in the echo of the target signal, and obtain the range-corrected echo signal; where

[0080] The expression of the range-corrected echo signal is as follows:

[0081]

[0082] σ ηrepresents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T a represents the pulse width, p(f τ ) represents the frequency-domain signal after Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential function with the natural number e as the base, j represents the imaginary unit, f τ represents the range frequency variable, f υ represents the carrier frequency of the radar signal, c represents the speed of light, f dr represents the Doppler frequency modulation rate, R 0 represents the range history at the initial time.

[0083] For S2, extract the azimuth signal of the same range cell from the range-corrected echo signal; obtain the de-chirped azimuth signal according to the azimuth signal of the same range cell and the corresponding de-chirping function.

[0084] The expression of the azimuth signal of the same range cell is as follows:

[0085]

[0086] where, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T a represents the pulse width, exp() represents the exponential function with the natural number e as the base, j represents the imaginary unit, f υ represents the carrier frequency of the radar signal, c represents the speed of light, f dr represents the Doppler frequency modulation rate, R 0 represents the range history at the initial time.

[0087] For S2, obtaining the de-chirped azimuth signal according to the azimuth signal of the same range cell and the corresponding de-chirping function may include:

[0088] Construct the de-chirping function according to the reconstructed azimuth time variable;

[0089] Multiply the azimuth signal of the same range cell by the de-chirping function to obtain the de-chirped azimuth signal.

[0090] Specifically, the expression of the de-chirping function is as follows:

[0091]

[0092] where, represents the de-chirping function, represents the new Doppler frequency modulation rate, which is determined by the coordinate positions of the target signal and the transceiver platform and the relative motion speed, η represents the reconstructed azimuth time variable, T arepresents the pulse width, exp() represents the exponential function with the natural number e as the base, and j represents the imaginary unit.

[0093] The expression of the de-chirped azimuth signal is as follows:

[0094]

[0095] S3. Divide the de-chirped azimuth signal into N frames along the azimuth direction to obtain the in-frame signals corresponding to each frame; perform azimuth Fourier transform processing on the in-frame signals corresponding to each frame to obtain the in-frame signals in the frequency domain; perform in-frame coherent and inter-frame non-coherent hybrid accumulation processing on the in-frame signals in the frequency domain to obtain the accumulated echo signal of the target signal.

[0096] Specifically, for S3, it may include:

[0097] S31. Divide the de-chirped azimuth signal into N frames along the azimuth direction to obtain the in-frame signals corresponding to each frame; where,

[0098] The expression of the in-frame signals corresponding to each frame is as follows:

[0099]

[0100] where, s n (f dr , η) represents the in-frame signal corresponding to the nth frame, N is the number of frames, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, exp() represents the exponential function with the natural number e as the base, j represents the imaginary unit, f υ represents the radar signal carrier frequency, c represents the speed of light, f dr represents the Doppler frequency modulation rate, R 0 represents the initial time range history, T CPI represents the duration of each frame, represents the new Doppler frequency modulation rate, which is determined by the coordinate positions and relative motion speeds of the target signal and the transceiver platform, n = -(N - 1) / 2,..., (N - 1) / 2, T CPI = T a / N.

[0101] S32. Perform azimuth Fourier transform processing on the in-frame signals corresponding to each frame to obtain the in-frame signals in the frequency domain; where,

[0102] The expression of the in-frame signals in the frequency domain is as follows:

[0103]

[0104] where, σ ηdenotes the complex scattering coefficient, rect() denotes the rectangular window function, η denotes the reconstructed azimuth time variable, T CPI denotes the duration of each frame, denotes the new Doppler modulation frequency, which is determined by the coordinate positions of the target signal and the transceiver platform and the relative motion speed, exp() denotes the exponential function with the natural number e as the base, j denotes the imaginary unit, f υ denotes the carrier frequency of the radar signal, c denotes the speed of light, f dr denotes the Doppler modulation frequency, R 0 denotes the range history at the initial moment, || denotes the modulus value, f η denotes the Doppler frequency, B denotes the bandwidth within a frame,

[0105] S33 performs intra-frame coherent and inter-frame non-coherent hybrid accumulation processing on the intra-frame signals in the frequency domain to obtain the accumulated echo signal of the target signal, which may include:

[0106] S331 removes the Doppler walk generated by the second-order phase term in the intra-frame signals in the frequency domain to obtain the optimal intra-frame accumulation effect.

[0107] Specifically, by taking the value as the value of f dr to remove the Doppler walk generated by the second-order phase term in the intra-frame signals in the frequency domain. At this time, the corresponding accumulation peak f η = 0, and the intra-frame signals are accumulated in the Doppler centroid-Doppler modulation frequency domain to to obtain the optimal intra-frame accumulation effect.

[0108] S332 performs non-coherent accumulation on the intra-frame signals in the frequency domain corresponding to all frames based on the optimal intra-frame accumulation effect to obtain the accumulated echo signal of the target signal.

[0109] The expression of the accumulated echo signal of the target signal is as follows:

[0110]

[0111] where, ∑ denotes the summation operation, f dr denotes the Doppler modulation frequency, f η denotes the Doppler frequency.

[0112] It can be understood that during the non-coherent accumulation process, by extracting the one-dimensional signal with f η = 0, the one-dimensional azimuth signal accumulation value is accumulated in the one-dimensional Doppler modulation frequency domain. Since only range compression cannot provide sufficient signal-to-noise ratio and the range cell where the target is located cannot be determined from the result of range compression, the above processing needs to be performed on the azimuth signals of all range cells, and the final accumulation result can be represented in the bistatic range-Doppler modulation frequency domain.

[0113] S4. Obtain the total echo signal based on the accumulated echo signal of the target signal; construct a Hankel matrix according to the total echo signal; perform singular value decomposition on the Hankel matrix to obtain the singular value matrix after clutter suppression; obtain the reconstructed echo matrix according to the singular value matrix after clutter suppression; perform slow-time Fourier transform on the reconstructed echo matrix to obtain the accumulated result after clutter suppression.

[0114] Specifically, S4 may include:

[0115] S41. Obtain the total echo signal based on the accumulated echo signal of the target signal; where

[0116] The expression of the total echo signal is as follows:

[0117]

[0118] represents the total echo signal, represents the accumulated echo signal of the target signal, represents the accumulated echo signal of the clutter, which is obtained by preprocessing the echo signal corresponding to the clutter. The process of preprocessing the echo signal corresponding to the clutter includes: sequentially performing positive and negative second-order keystone transforms, de-chirping, and intra-frame and inter-frame coherent processing on the echo signal corresponding to the clutter to obtain the accumulated echo signal of the clutter.

[0119] S42. Construct a Hankel matrix according to the total echo signal, which may include:

[0120] S421. Perform inverse Fourier transform on the total echo signal to obtain the slow-time time-domain echo; where

[0121] For the total echo signal perform inverse Fourier transform to obtain the slow-time time-domain echo η 1 ∈{1, 2,..., N}, η 1 is the slow-time variable corresponding to f η

[0122] S422. Construct a Hankel matrix according to the slow-time time-domain echo, including:

[0123] Extract the slow-time column vector s (:, η″) from the slow-time time-domain echo a (:, η″).

[0124] Use the slow-time column vector s a (:, η″) to construct the Hankel matrix s H ; where

[0125] ​Hankel matrix s H The expression is as follows:

[0126]

[0127] O represents the number of columns of the Hankel matrix, O ∈ {1, 2,..., N / 2}, and N represents the number of frames into which the de-chirped azimuth signal is divided.

[0128] S43. Perform singular value decomposition on the Hankel matrix to obtain a singular value matrix after clutter suppression, which may include:

[0129] S431. Perform singular value decomposition on the Hankel matrix based on the left and right singular value unitary matrices to obtain a singular value diagonal matrix.

[0130] The expression of the Hankel matrix is as follows:

[0131] s H = UΣV H ;

[0132] Among them, U represents the left singular value unitary matrix, V represents the right singular value unitary matrix, V H represents the conjugate transpose matrix of V, and Σ represents the singular value diagonal matrix.

[0133] It can be understood that after performing singular value decomposition on the Hankel matrix using the left and right singular value unitary matrices, the corresponding singular value diagonal matrix Σ can be obtained.

[0134] S432. Calculate the difference between adjacent singular values in the singular value diagonal matrix, determine the points where the difference change exceeds a preset threshold, and set the singular values after these points to zero to obtain a singular value matrix after clutter suppression.

[0135] By determining the points where the difference change exceeds the preset threshold, the smaller singular values in the singular value diagonal matrix can be set to zero, and the preset threshold can be freely set according to the actual usage requirements.

[0136] S44. Obtain a reconstructed echo matrix based on the singular value matrix after clutter suppression.

[0137] The expression of the reconstructed echo matrix is as follows:

[0138] s' H = U s Σ s V s H ;

[0139] Among them, s' H represents the reconstructed echo matrix, U s represents the new left singular value matrix, V s represents the new right singular value matrix, V sH Denote V s as the conjugate transpose matrix of V, and Σ s denotes the singular value matrix after clutter suppression.

[0140] It can be understood that the new left singular value matrix U s and the new right singular value matrix V s can be determined according to the singular value matrix after clutter suppression.

[0141] S45. Perform slow-time Fourier transform on the reconstructed echo matrix to obtain the accumulated result after clutter suppression.

[0142] In the embodiments of the present invention, to solve the problems of cross-range cell and cross-Doppler cell existing in radar target echo signals, a long-time accumulation method of in-frame coherent and inter-frame non-coherent hybrid accumulation is adopted to achieve energy aggregation, and clutter suppression is achieved by reconstructing the singular value matrix.

[0143] Next, through specific simulation experiments, the beneficial effects of a method for pulse accumulation and clutter suppression of spaceborne radar sea surface target signals proposed in the embodiments of the present invention are further verified.

[0144] Simulation conditions

[0145] The environment for the simulation experiment in the embodiments of the present invention is: Intel(R) Core(TM) i7-10700 CPU@2.90GHz 2.90GHz, Windows Professional Edition.

[0146] Simulation content and result analysis

[0147] Use simulation data to verify the effectiveness of the algorithm.

[0148] The simulation verification shows that the radar signal bandwidth is 10.23 MHz, the carrier frequency is 1.27 GHz, the speed of the spaceborne platform is 7900 m / s, the pulse repetition frequency is 500 Hz, the sampling frequency is 50 MHz, the accumulation duration is 60 s, the target speed is 15 knots, and the K-distributed sea clutter at sea state 3 is used as the observation scenario.

[0149] For the effect diagram of long-time pulse accumulation of moving targets in the clutter background in the embodiments of the present invention, please refer to Figure 2 as shown. It can be seen from Figure 2 that the embodiments of the present invention can significantly improve the clutter suppression performance and overcome the problem of insufficient moving target detection performance of existing spaceborne radars due to the influence of clutter in echo signals.

[0150] In the embodiments of the present invention, a second-order Keystone transform is utilized to reconstruct the azimuth-time variable to obtain the echo signal after range correction. The de-chirp function is used to process the azimuth signal extracted from the echo signal after range correction for the same range cell to achieve de-chirping of the azimuth signal. By performing intra-frame coherent and inter-frame non-coherent hybrid accumulation processing on the intra-frame signal in the decomposed frequency domain, the echo signal containing the target signal and clutter is obtained, optimizing the problems of cross-range and Doppler cell in the long-time accumulation of moving targets. Based on the inverse Fourier transform of the echo signal containing the target signal and clutter, the singular value matrix after clutter suppression is obtained, and the slow-time Fourier transform is performed on the reconstructed echo matrix to obtain the accumulation result after clutter suppression, solving the problem of insufficient moving target detection performance of existing spaceborne radars due to the influence of clutter in the echo signal. This enables the present invention to have the capabilities of cross-range cell correction, cross-Doppler cell correction, long-time energy accumulation, and clutter suppression in engineering practice, improving the accuracy of moving target detection in the clutter background of spaceborne radars.

[0151] It should be noted that in the description of the present invention, it should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality" means two or more, unless otherwise specifically defined.

[0152] The above are only the preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.

Claims

1. A method for pulse accumulation and clutter suppression of sea surface target signals of spaceborne radar, characterized in that: include: Based on the distance history of the target signal, the azimuth time variable is reconstructed using the second-order keystone transform to obtain the echo signal after distance correction. Extracting the azimuth signal of the same distance unit from the distance-corrected echo signal; obtaining the de-frequency-modulated azimuth signal according to the azimuth signal of the same distance unit and the corresponding de-frequency-modulation function; The de-frequency modulated azimuth signal is divided into N frames along the azimuth direction to obtain the intra-frame signal corresponding to each frame; the intra-frame signal corresponding to each frame is processed by azimuth Fourier transform to obtain the intra-frame signal in the frequency domain; the intra-frame signal in the frequency domain is processed by intra-frame coherent and inter-frame non-coherent mixed accumulation to obtain the accumulated echo signal of the target signal; A total echo signal is obtained based on the accumulated echo signal of the target signal; a Hankel matrix is ​​constructed according to the total echo signal; a singular value decomposition is performed on the Hankel matrix to obtain a singular value matrix after clutter suppression; a reconstructed echo matrix is ​​obtained according to the singular value matrix after clutter suppression; a slow-time Fourier transform is performed on the reconstructed echo matrix to obtain an accumulated result after clutter suppression.

2. The method for pulse accumulation and clutter suppression of sea surface target signals by satellite-borne radar according to claim 1, characterized in that: The method of reconstructing the azimuth time variable based on the distance history of the target signal by using the second-order keystone transform to obtain the echo signal after distance correction includes: According to the distance history of the target signal and the wavelength corresponding to the carrier frequency, a Doppler phase caused by the distance history of the target signal is obtained, and according to the Doppler phase, an instantaneous Doppler frequency of the target is obtained; Based on the instantaneous Doppler frequency of the target, the echo signal corresponding to the target signal after the range is Fourier transformed is determined as the echo signal in the frequency domain; wherein, The expression of the echo signal in the frequency domain is as follows: f dc represents the Doppler centroid, f dr represents the Doppler modulation frequency, f d3 represents the third-order Doppler, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η′ represents the azimuth time, T a Indicates the pulse width, p(f τ ) represents the frequency domain signal after the Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f τ represents the distance frequency variable, f υ represents the radar signal carrier frequency, c represents the speed of light, and R0 represents the distance history at the initial moment; The azimuth-time variables are reconstructed using positive second-order keystone transform; A distance-corrected echo signal is obtained based on the frequency-domain echo signal and the reconstructed azimuth-time variable.

3. The method for pulse accumulation and clutter suppression of sea surface target signals by satellite-borne radar according to claim 2, characterized in that: Obtaining a distance-corrected echo signal based on the echo signal in the frequency domain and the reconstructed azimuth time variable includes: According to the reconstructed azimuth-time variables, the positive and negative second-order keystone transform is used to remove the coupling between the range frequency and the azimuth-time in the echo signal in the frequency domain, and the echo signal after range correction is obtained; wherein, The expression of the echo signal after distance correction is as follows: σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T a Indicates the pulse width, p(f τ ) represents the frequency domain signal after the Fourier transform of the fundamental wave of the LFM signal, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f τ represents the distance frequency variable, f υ represents the radar signal carrier frequency, c represents the speed of light, and f dr represents the Doppler modulation frequency, and R0 represents the distance history at the initial moment.

4. The method for pulse accumulation and clutter suppression of sea surface target signals by satellite-borne radar according to claim 1, characterized in that: The expression of the azimuth signal of the same distance unit is as follows: Among them, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T a represents the pulse width, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f υ represents the radar signal carrier frequency, c represents the speed of light, and f dr represents the Doppler modulation frequency, and R0 represents the distance history at the initial moment.

5. The method for pulse accumulation and clutter suppression of sea surface target signals by spaceborne radar according to claim 1, characterized in that: The step of obtaining a de-frequency modulated azimuth signal according to the azimuth signal of the same distance unit and the corresponding de-frequency modulation function comprises: constructing a de-frequency modulation function according to the reconstructed azimuth time variable; The azimuth signal of the same distance unit is multiplied by the de-frequency modulation function to obtain a de-frequency modulation azimuth signal.

6. The method for pulse accumulation and clutter suppression of sea surface target signals by spaceborne radar according to claim 1, characterized in that: The expression of the intra-frame signal corresponding to each frame is as follows: Among them, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f υ represents the radar signal carrier frequency, c represents the speed of light, and f dr represents the Doppler modulation frequency, R0 represents the distance history at the initial moment, T CPI Indicates the duration of each frame. represents the new Doppler modulation rate, which is determined by the coordinate position and relative motion speed of the target signal and the transceiver platform, n = -(N-1) / 2,...,(N-1) / 2.

7. The method for pulse accumulation and clutter suppression of sea surface target signals by spaceborne radar according to claim 1, characterized in that: The expression of the intra-frame signal in the frequency domain is as follows: Among them, σ η represents the complex scattering coefficient, rect() represents the rectangular window function, η represents the reconstructed azimuth time variable, T CPI Indicates the duration of each frame. represents the new Doppler modulation rate, which is determined by the coordinate position and relative speed of the target signal and the transceiver platform. exp() represents the exponential with the natural number e as the base, j represents the imaginary unit, and f υ represents the radar signal carrier frequency, c represents the speed of light, and f dr represents the Doppler modulation frequency, R0 represents the distance history at the initial moment, | | represents the modulus value, and f η represents the Doppler frequency, B represents the intra-frame bandwidth, 8. The method for pulse accumulation and clutter suppression of sea surface target signals of a space-borne radar according to claim 7, characterized in that: The method of performing intra-frame coherent and inter-frame non-coherent mixed accumulation processing on the intra-frame signal in the frequency domain to obtain the accumulated echo signal of the target signal includes: The Doppler movement caused by the second-order phase term in the intra-frame signal in the frequency domain is removed to obtain the optimal intra-frame accumulation effect; Based on the optimal intra-frame accumulation effect, incoherent accumulation is performed on the intra-frame signals in the frequency domain corresponding to all frames to obtain the accumulated echo signals of the target signals.

9. The method for pulse accumulation and clutter suppression of sea surface target signals by spaceborne radar according to claim 1, characterized in that: Performing singular value decomposition on the Hankel matrix to obtain a singular value matrix after clutter suppression, including: Performing singular value decomposition on the Hankel matrix based on the left and right singular value unitary matrices to obtain a singular value diagonal matrix; The differences of adjacent singular values ​​in the singular value diagonal matrix are calculated, and the points where the difference changes exceed the preset threshold are determined. The singular values ​​after this point are set to zero to obtain the singular value matrix after clutter suppression.

10. The method for pulse accumulation and clutter suppression of sea surface target signals of spaceborne radar according to claim 9, characterized in that: The expression of the reconstructed echo matrix is ​​as follows: s′ H =U s S s V s H ; Among them, s′ H represents the reconstructed echo matrix, U s The new left singular value matrix, V s represents the new right singular value matrix, V s H represents the transpose of the new right singular value matrix, Σ s Represents the singular value matrix after clutter suppression.

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