Efficient space-time processing method for multi-channel radar foresight imaging

Abstract

The invention discloses an efficient space-time processing method for multi-channel radar foresight imaging, which comprises the following steps of: firstly, acquiring multi-channel foresight radar echo data of an area to be imaged, and performing range pulse compression and range migration correction on the acquired data; the method comprises the following steps: firstly, carrying out space-time super-resolution and space-time beamforming on each channel, then separating echoes along a track area and deviating from a track area in each channel by using Doppler differences of different areas, finally, constructing different space-time guide matrixes for different echo data, respectively realizing imaging through space-time super-resolution and space-time beamforming processing, and further obtaining a final imaging result through splicing processing. According to the method, the calculation burden of multi-channel radar foresight super-resolution imaging is remarkably reduced, the space-variant problem of a point spread function is indirectly solved, and excellent imaging performance can be obtained.

Description

Technical Field

[0001] This invention belongs to the field of radar imaging technology, specifically relating to an efficient spatiotemporal processing method for multi-channel radar forward-looking imaging. Background Technology

[0002] Forward-looking radar imaging has important applications in autonomous landing, autonomous navigation and other fields. However, conventional single-channel SAR or Doppler beam sharpening technology has blind spots in forward-looking imaging due to Doppler symmetry blurring and small Doppler changes in the forward-looking region.

[0003] To improve the angular resolution and resolution of left-right ambiguity in the region along the flight path, the paper "J. Lu, L. Zhang, S. Wei, and Y. Li, 'Resolution enhancement for forwarding looking multi-channel SAR imagery with exploiting space-time sparsity,' IEEE Transactions on Geoscience and Remote Sensing, vol. 61, pp. 1–17, 2023" introduces the sparse Bayesian reconstruction method into the temporal imaging results with left-right ambiguity, achieving improved angular resolution and resolution of left-right ambiguity. However, its imaging performance is still affected by the focusing results of single-channel SAR. Especially in the region along the flight path, the azimuth main lobe widens significantly, and adjacent azimuth cells are affected by strong cross-interference, leading to a decrease in left-right ambiguity resolution. Furthermore, the paper "W. Li, R. Chen, J. Yang, J. Wu, Y. Zhang, and Y. Huang, 'A hybrid real / synthetic aperture scheme for multichannel radar forward-looking superresolution imaging,' IEEE Geoscience and Remote Sensing Letters, vol. 20, pp. 1–5, 2023" achieves angular super-resolution in the echo domain using single snapshot data, and then fuses the results with single-channel synthetic aperture imaging to achieve forward-looking imaging. However, the super-resolution performance provided by single snapshot data is usually limited by the signal-to-noise ratio (SNR) and the number of channels. To improve super-resolution performance, the paper "R. Chen, W. Li, J. Yang, K. Li, K. Zhang, and J. Wu, 'Time–frequency–spacesteering matrix-based left / right ambiguity resolving for dual-channel forward-looking SAR imaging,' IEEE Transactions on Geoscience and RemoteSensing, vol. 62, pp. 1–12, 2024" constructs a space-time steering matrix, establishes a linear equation between the echo and scattering coefficients, and reconstructs the forward-looking scene by solving the equation. However, the space-time super-resolution model involves calculating large sample covariance matrices and corresponding matrix operations, resulting in extremely high computational complexity.Furthermore, due to the issue that the point spread function varies with the azimuth angle, the corresponding super-resolution algorithms often fail to achieve a good balance between maintaining good reconstruction performance in the off-track region and good angular resolution performance in the along-track region. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention provides an efficient space-time processing method for multi-channel radar forward-looking imaging, aiming to reduce the computational burden in the super-resolution process and indirectly overcome the spatial variation problem of the point spread function, thereby achieving better super-resolution performance.

[0005] The technical solution adopted in this invention is: an efficient space-time processing method for multi-channel radar forward-looking imaging, the specific steps of which are as follows:

[0006] S1. Acquire multi-channel forward-looking radar echo data of the area to be imaged;

[0007] Multi-channel radar forward-looking imaging employs a single-transmit, multi-receiver channel configuration, meaning one channel transmits the signal while multiple channels receive it; this is used in scenarios where any point target exists. The coordinates are Then its historical distance from the launch channel Distance history of receiving channel The expressions are as follows:

[0008] ;

[0009] ;

[0010] in, Representing the target Coordinates in the Cartesian coordinate system Indicates the platform's flight speed. Indicates the platform's flight altitude. and Representing a point target Relative to the transmitting antenna The slant range and azimuth, Indicates the angle between the target's line of sight and the vertical direction. Indicates slow time. Indicates the first The azimuth coordinates of the root receiving antenna. , This indicates the floor function. Indicates the channel spacing. Indicates the number of antennas.

[0011] For point targets Its round-trip distance history The expression is as follows:

[0012] ;

[0013] If the transmitted signal is set to a linear frequency modulated pulse, then the echo signals received by multiple channels... The expression is as follows:

[0014] ;

[0015] in, This represents the scattering coefficient of the target. Indicates distance frequency modulation. Represents the speed of light. Indicates the wavelength of the transmitted signal. It indicates a fast time.

[0016] S2. Perform range pulse compression and range migration correction on the echo data obtained in step S1;

[0017] Set the matching function for pulse compression as follows: The signal after pulse compression The expression is as follows:

[0018] ;

[0019] Wherein, IFFT represents the inverse Fourier transform operator, and FFT represents the Fourier transform operator;

[0020] Then, perform a range Fourier transform on equation (5) to obtain the echo signal in the range frequency domain. The expression is as follows:

[0021] ;

[0022] in, =FT[ ], Indicates the bandwidth of the LFM pulse. Indicates the carrier frequency. Indicates distance frequency.

[0023] Then select the azimuth angle as °, slant distance is The point target is used as a reference target, and its coordinates are... The echo signal after phase compensation The expression is as follows:

[0024] ;

[0025] Then, the Keystone transform is used to implement the linear distance migration correction (RCM), which is a scaling transformation of slow time, as shown in the following expression:

[0026] ;

[0027] in, This represents the slow time after scaling.

[0028] Substituting equation (8) into equation (7) and performing an inverse Fourier transform of the distance, the echo after RCM is obtained. The expression is as follows:

[0029] ;

[0030] Then the echo of a range cell The expression is as follows:

[0031] ;

[0032] Then, in equation (10) Perform a Taylor expansion, retaining the first-order terms, as shown in the following expression:

[0033] ;

[0034] Finally, substituting equation (11) into equation (10), the echo of a range cell is obtained. The expression is as follows:

[0035] ;

[0036] The first term is a constant, the second term represents the path difference phase related to the spatial channel, and the third term represents the phase related to the synthetic aperture.

[0037] S3. Based on the Doppler differences in different imaging regions, separate the echo data processed in step S2.

[0038] The cutoff frequency is designed based on the critical angle, and then low-pass filtering is performed on each channel to separate the echoes along the track and those off the track.

[0039] S4. Based on the echo data of different imaging regions obtained in step S3, different imaging schemes are executed, and the final imaging result is obtained by stitching together the imaging results of the two regions along the track and off the track.

[0040] Among them, echoes along the flight path region are subjected to space-time super-resolution processing, while echoes deviating from the flight path region are subjected to space-time beamforming processing.

[0041] Furthermore, step S3 is specifically as follows:

[0042] According to equation (12), the approximate expressions for echo data in different regions within a single distance cell are as follows:

[0043] ;

[0044] ;

[0045] in, , , as well as , , These represent the echo, scattering coefficient, and azimuth angle along the flight path and off the flight path, respectively.

[0046] Design a low-pass filter to detect echoes. Extracting echoes along the flight path The cutoff frequency of a low-pass filter is the corresponding Doppler frequency. .

[0047] in, The critical angle represents the boundary between the deviation from the track area and the track area, determined based on the trend of angular resolution variation; and the angular resolution of multi-channel radar forward-looking imaging is expressed as the 3dB width of the angular ambiguity function. Therefore, according to equation (12), the angular ambiguity function of multi-channel radar forward-looking imaging... The expression is as follows:

[0048] ;

[0049] in, Indicates the azimuth of the target. This indicates the angular resolution of the multi-channel forward-looking SAR. Indicated Conjugate.

[0050] Equation (15) is integrated to obtain the variation curve of the angular ambiguity function. Then, its 3dB variation range is truncated. The approximate expression of the angular resolution of the multi-channel forward-looking SAR is as follows:

[0051] ;

[0052] in, Indicates the synthetic aperture length. Indicates the actual aperture length.

[0053] Then, the azimuth angle in equation (16) Find the partial derivative, the expression is as follows:

[0054] ;

[0055] Among them, the critical angle is determined when the value of equation (17) is less than the empirical threshold, with the system parameters fixed.

[0056] Finally, the same low-pass filter was used on the echo data of each channel to obtain the echo data along the track area. Then, the echo data deviating from the track area is obtained by subtracting the echo data along the track area from the complete echo data. .

[0057] Furthermore, step S4 is specifically as follows:

[0058] First, the echoes of different regions corresponding to equations (13) and (14) are rewritten in discrete form, as shown in the following expressions:

[0059] ;

[0060] in, , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector, respectively, which deviate from the track area. , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector along the flight path, respectively.

[0061] Then guide matrix Represented as the Kronecker product of spatial and temporal vectors, the grid point vectors deviating from the flight path region are defined as follows: The specific expression for the guidance matrix is ​​as follows:

[0062] ;

[0063] in, , , , , Indicates the synthetic aperture sampling interval. The number of sampling points indicates the synthetic aperture. This indicates the number of antennas, i.e., the number of channels. This indicates the transpose operation.

[0064] Similarly, the grid point vectors along the flight path region are... Substitute equation (19) to construct the corresponding guidance matrix. Then, for areas deviating from the flight path, space-time beamforming is introduced to achieve azimuth focusing for each range cell, as shown in the following expression:

[0065] ;

[0066] in, Indicates the imaging results, This indicates the conjugate transpose operation.

[0067] For the area along the flight path, an iterative optimization algorithm is used to enhance imaging performance. Specifically, for echo data of a certain range cell, an iterative adaptive algorithm is used to solve the constructed spatiotemporal linear observation equation. The specific calculation process is as follows:

[0068] 1) Calculation ;

[0069] 2) Calculate the covariance matrix ;

[0070] 3) Update ;

[0071] 4) Return to step 1).

[0072] in, Represents the scattering coefficient matrix. Indicates the first Each scattering coefficient; This indicates the number of grid points divided along the flight path area. yes The Column vectors Represents the regularization parameter. Represents the identity matrix.

[0073] After multiple iterations of steps 1)-4) to obtain converged results, the same operation is performed on the echo data of all range cells to obtain the imaging results along the track region. .

[0074] Finally, the final imaging result is obtained by stitching together the imaging results from the areas along the flight path and those deviating from the flight path.

[0075] The beneficial effects of this invention are as follows: The method of this invention first acquires multi-channel forward-looking radar echo data of the area to be imaged. Range pulse compression and range migration correction are then performed on the acquired data. Next, the Doppler differences between different regions are used to separate the echoes along the track and those deviating from the track in each channel. Finally, different space-time steering matrices are constructed for different echo data, and imaging is achieved through space-time super-resolution and space-time beamforming processes, respectively. The final imaging result is then obtained through stitching. This method significantly reduces the computational burden of multi-channel radar forward-looking super-resolution imaging, indirectly overcomes the spatial variation problem of the point spread function, and achieves excellent imaging performance. Attached Figure Description

[0076] Figure 1 This is a flowchart of an efficient space-time processing method for multi-channel radar forward-looking imaging according to the present invention.

[0077] Figure 2 This is a schematic diagram of the geometric model of multi-channel radar forward-looking imaging in an embodiment of the present invention.

[0078] Figure 3 This is a schematic diagram of the observation scene in an embodiment of the present invention.

[0079] Figure 4 This is a flowchart of the regional processing in an embodiment of the present invention.

[0080] Figure 5 This is a schematic diagram of the spatiotemporal super-resolution result after the echo is separated in an embodiment of the present invention.

[0081] Figure 6 This is a schematic diagram of the spatiotemporal beamforming result after the echo is separated in an embodiment of the present invention.

[0082] Figure 7 This is a schematic diagram of the imaging results using the method of the present invention in an embodiment of the present invention. Detailed Implementation

[0083] The method of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0084] like Figure 1 The flowchart shown is a method for efficient space-time processing of multi-channel radar forward-looking imaging according to the present invention. The specific steps are as follows:

[0085] S1. Acquire multi-channel forward-looking radar echo data of the area to be imaged;

[0086] The forward-looking radar employs a single-transmitter, multiple-receiver channel configuration, meaning one channel transmits the signal and multiple channels receive the signal. In this embodiment, the geometric configuration of the forward-looking multi-channel radar is as follows: Figure 2 As shown in Table 1, the parameters of the forward-looking multi-channel radar are as follows.

[0087] Table 1

[0088]

[0089] The scene contains any point target. The coordinates are Then its historical distance from the launch channel Distance history of receiving channel The expressions are as follows:

[0090] ;

[0091] ;

[0092] in, Representing the target Coordinates in the Cartesian coordinate system Indicates the platform's flight speed. Indicates the platform's flight altitude. and Representing a point target Relative to the transmitting antenna The slant range and azimuth, Indicates the angle between the target's line of sight and the vertical direction. Indicates slow time. Indicates the first The azimuth coordinates of the root receiving antenna. , This indicates the floor function. Indicates the channel spacing. Indicates the number of antennas.

[0093] For point targets Its round-trip distance history The expression is as follows:

[0094] ;

[0095] If the transmitted signal is set to a linear frequency modulated pulse, then the echo signals received by multiple channels... The expression is as follows:

[0096] ;

[0097] in, This represents the scattering coefficient of the target. Indicates distance frequency modulation. Represents the speed of light. Indicates the wavelength of the transmitted signal. It indicates a fast time.

[0098] like Figure 2 As shown, in one In a spatial coordinate system, The origin of the coordinate system is indicated by the speed of the multi-channel forward-looking radar. ,high along It flies at a constant speed in a straight line along the axial direction, forming a length of The synthetic aperture. The center position of the target scene is... , , That is, the pitch angle between the aircraft and the center of the scene is On the platform, the launch channel and receiving channel along axial direction The spacing arrangement, With pulse repetition frequency Transmit signal, and Simultaneously receive signals.

[0099] In this embodiment, the radar transmission wavelength is set to... The pulse width is bandwidth is The linear frequency modulated pulse signal, the distance between a single snapshot and the sampling points The number of channels is 512. The number of sampling points for the synthetic aperture dimension is 5. The signal-to-noise ratio of the echo after pulse compression is 512. .

[0100] The original scene simulated in this embodiment is as follows: Figure 3 As shown, the azimuth range of the observation scene is Distance length azimuth coordinates of the receiving antenna , , , , For each channel, the azimuth angle is divided according to the observation scene. and distance sampling points The scene can be evenly divided into The grid is used to calculate the two-way distance history using equations (1), (2), and (3). Then, the echo signal is calculated using equation (4). .

[0101] S2. Perform range pulse compression and range migration correction on the echo data obtained in step S1;

[0102] Set the matching function for pulse compression as follows: The signal after pulse compression The expression is as follows:

[0103] ;

[0104] Wherein, IFFT represents the inverse Fourier transform operator, and FFT represents the Fourier transform operator;

[0105] Then, perform a range Fourier transform on equation (5) to obtain the echo signal in the range frequency domain. The expression is as follows:

[0106] ;

[0107] in, =FT[ ], Indicates the bandwidth of the LFM pulse. Indicates the carrier frequency. Indicates distance frequency.

[0108] Then select the azimuth angle as °, slant distance is The point target is used as a reference target, and its coordinates are... The echo signal after phase compensation The expression is as follows:

[0109] ;

[0110] Then, the Keystone transform is used to implement the linear distance migration correction (RCM), which is a scaling transformation of slow time, as shown in the following expression:

[0111] ;

[0112] in, This represents the slow time after scaling.

[0113] Substituting equation (8) into equation (7) and performing an inverse Fourier transform of the distance, the echo after RCM is obtained. The expression is as follows:

[0114] ;

[0115] Then the echo of a range cell The expression is as follows:

[0116] ;

[0117] Then, in equation (10) Perform a Taylor expansion, retaining the first-order terms, as shown in the following expression:

[0118] ;

[0119] Finally, substituting equation (11) into equation (10), the echo of a range cell is obtained. The expression is as follows:

[0120] ;

[0121] The first term is a constant, the second term represents the path difference phase related to the spatial channel, and the third term represents the phase related to the synthetic aperture.

[0122] This embodiment is first based on the sampling rate. and distance sampling point The fast time was calculated. The sequence is then used to obtain the matching function for pulse compression. Based on the echo data generated in step S1, the result of echo pulse compression is obtained using equation (5). Based on equation (5), a Fourier transform is performed on the fast time dimension to obtain the echo signal with distance frequency as shown in equation (6). Then, take the target at the very center of the scene, i.e., at coordinates... , , The target is used as a reference target, and the phase-compensated signal is obtained by combining Equation (6), as shown in Equation (7). Considering that the range curvature is usually small, the first-order keystone transform is used to realize linear range cell migration (RCM) correction. Equation (8) is used to perform a scale transformation on the slow time, and then combined with the inverse Fourier transform of the range, the echo signal after RCM is obtained. As shown in equation (9). Furthermore, in order to accelerate the subsequent execution process, equation (9) is approximated as equation (12), which is beneficial for constructing the steering matrix using the Kronecker product.

[0123] S3. Based on the Doppler differences in different imaging regions, separate the echo data processed in step S2.

[0124] The cutoff frequency is designed based on the critical angle, and then low-pass filtering is performed on each channel to separate the echoes along the track and those off the track.

[0125] According to equation (12), the approximate expressions for echo data in different regions within a single distance cell are as follows:

[0126] ;

[0127] ;

[0128] in, , , as well as , , These represent the echo, scattering coefficient, and azimuth angle along the flight path and off the flight path, respectively.

[0129] It can be seen that the echoes from targets in different areas are related to the azimuth angle, especially... and This is related to the Doppler frequency. For targets along the flight path, the Doppler frequency is typically lower. Conversely, for targets deviating from the flight path, the Doppler frequency is typically higher. Therefore, a low-pass filter is designed to detect the Doppler frequency from the echo. Extracting echoes along the flight path The cutoff frequency of a low-pass filter is the corresponding Doppler frequency. .

[0130] Among them, the cutoff frequency of the filter is determined by the critical angle. Sure, That is, the boundary point between the deviation area and the along-track area is determined based on the trend of angular resolution change; according to the fuzzy function theory, the angular resolution of multi-channel radar forward-looking imaging is expressed as the 3dB width of the angular fuzzy function, then according to equation (12), the angular fuzzy function of multi-channel radar forward-looking imaging The expression is as follows:

[0131] ;

[0132] in, Indicates the azimuth of the target. This indicates the angular resolution of the multi-channel forward-looking SAR. Indicated Conjugate.

[0133] Equation (15) is integrated to obtain the variation curve of the angular ambiguity function. Then, its 3dB variation range is truncated. The approximate expression of the angular resolution of the multi-channel forward-looking SAR is as follows:

[0134] ;

[0135] in, Indicates the synthetic aperture length. Indicates the actual aperture length.

[0136] From equation (16), it can be seen that when parameters such as the synthetic aperture length and the actual aperture length are fixed, the angular resolution is mainly related to the azimuth angle. As the azimuth angle increases, the angular resolution will gradually increase, and the trend of the angular resolution change follows... The function is characterized by a rapid initial change followed by a slower one. To more intuitively grasp the trend of change, the azimuth angle in equation (16) is analyzed. Find the partial derivative, the expression is as follows:

[0137] ;

[0138] Among them, the critical angle is determined when the value of equation (17) is less than the empirical threshold, with the system parameters fixed.

[0139] Furthermore, considering the small actual aperture and the small difference in Doppler frequencies between different channels, the same low-pass filter was used for the echo data of each channel to obtain echo data along the flight path region. Then, the echo data deviating from the track area is obtained by subtracting the echo data along the track area from the complete echo data. .

[0140] In this embodiment, the parameters from Table 1 are first substituted into equation (17) to obtain the trend of azimuth variation. Then, by selecting points where the absolute value change is less than 0.05, azimuth 3° is chosen as the dividing point between the along-track area and the deviation from the flight path. This dividing point is then substituted into equation (17). The cutoff frequencies for different regions are obtained, and low-pass filters for separating the regions along the flight path can be designed. Furthermore, low-pass filtering is performed on the data of each channel to obtain echo data along the flight path, as shown in Equation (13). Finally, the difference between the echo data without low-pass filtering and the echo data with low-pass filtering is used to obtain echo data deviating from the flight path, as shown in Equation (14).

[0141] S4. Based on the echo data of different imaging regions obtained in step S3, different imaging schemes are executed, and the final imaging result is obtained by stitching together the imaging results of the two regions along the track and off the track.

[0142] Among them, echoes along the flight path region are subjected to space-time super-resolution processing, while echoes deviating from the flight path region are subjected to space-time beamforming processing.

[0143] First, the echoes of different regions corresponding to equations (13) and (14) are rewritten in discrete form, as shown in the following expressions:

[0144] ;

[0145] in, , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector, respectively, which deviate from the track area. , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector along the flight path, respectively.

[0146] Then guide matrix Represented as the Kronecker product of spatial and temporal vectors, the grid point vectors deviating from the flight path region are defined as follows: The specific expression for the guidance matrix is ​​as follows:

[0147] ;

[0148] in, , , , , Indicates the synthetic aperture sampling interval. The number of sampling points indicates the synthetic aperture. This indicates the number of antennas, i.e., the number of channels. This indicates the transpose operation.

[0149] Similarly, the grid point vectors along the flight path region are... Substitute equation (19) to construct the corresponding guidance matrix. Then, for areas deviating from the flight path, space-time beamforming is introduced to achieve azimuth focusing for each range cell, as shown in the following expression:

[0150] ;

[0151] in, Indicates the imaging results, This indicates the conjugate transpose operation.

[0152] For the area along the flight path, due to the small Doppler variation, the angular resolution and left / right ambiguity resolution performance are poor. An iterative optimization algorithm is used to enhance imaging performance. Specifically, for echo data of a certain range cell, an iterative adaptive algorithm is used to solve the constructed spatiotemporal linear observation equation. The specific calculation process is as follows:

[0153] 1) Calculation ;

[0154] 2) Calculate the covariance matrix ;

[0155] 3) Update ;

[0156] 4) Return to step 1).

[0157] in, Represents the scattering coefficient matrix. Indicates the first Each scattering coefficient; This indicates the number of grid points divided along the flight path area. yes The Column vectors Represents the regularization parameter. Represents the identity matrix.

[0158] After multiple iterations of steps 1)-4) to obtain converged results, the same operation is performed on the echo data of all range cells to obtain the imaging results along the track region. .

[0159] Finally, the final imaging result is obtained by stitching together the imaging results from the areas along the flight path and those deviating from the flight path.

[0160] In this embodiment, the regional processing approach of the method of the present invention is as follows: Figure 4 As shown, for echo data deviating from the track area, space-time beamforming processing is applied. For echo data along the track area, space-time super-resolution processing is applied. Therefore, based on the separated echo data, as shown in equations (13) and (14), they can be rewritten in the discrete form shown in equation (18). and For the grid points in the region, the corresponding path difference and Doppler variation steering vectors are generated using equation (19), and then the steering matrix deviating from the track region is generated using the Kronecker product. Similarly, for The grid points are also used to construct corresponding guidance vectors, thereby forming a guidance matrix along the flight path region. .

[0161] Then, different imaging schemes are introduced for different imaging regions. On the one hand, for echo data deviating from the flight path area... Using the guidance matrix Perform space-time beamforming processing to obtain the corresponding imaging results. As in equation (20) and Figure 5 As shown. On the other hand, for echo data along the flight path area... The solution is obtained using a super-resolution iterative approach. The number of iterations is set to 15, and the regularization coefficient is [value missing]. By performing the same iterative operation on all range cells, the final super-resolution image can be obtained. Just like Figure 6 As shown. Ultimately, will and Perform stitching processing to obtain the imaging results of the forward-looking area, such as... Figure 7 As shown.

[0162] In summary, the method of this invention significantly reduces the computational burden of forward-looking super-resolution imaging of multi-channel radar, indirectly overcomes the spatial variation problem of the point spread function, and can obtain excellent imaging performance.

[0163] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the implementation methods of the present invention, and should be understood that the scope of protection of the present invention is not limited to such specific statements and embodiments. Those skilled in the art can make various other specific modifications and combinations based on the technical teachings disclosed in this invention without departing from the spirit of the invention, and these modifications and combinations are still within the scope of protection of the present invention.

Claims

1. An efficient space-time processing method for forward-looking imaging of multi-channel radar, comprising the following steps: S1. Acquire multi-channel forward-looking radar echo data of the area to be imaged; Multi-channel radar forward-looking imaging employs a single-transmit, multi-receiver channel configuration, meaning one channel transmits the signal while multiple channels receive it; this is used in scenarios where any point target exists. The coordinates are Then its historical distance from the launch channel Distance history of receiving channel The expressions are as follows: ； ； in, Representing the target Coordinates in the Cartesian coordinate system Indicates the platform's flight speed. Indicates the platform's flight altitude. and Representing a point target Relative to the transmitting antenna The slant range and azimuth, Indicates the angle between the target's line of sight and the vertical direction. Indicates slow time. Indicates the first The azimuth coordinates of the root receiving antenna. , This indicates the floor function. Indicates the channel spacing. Indicates the number of antennas; For point targets Its round-trip distance history The expression is as follows: ； If the transmitted signal is set to a linear frequency modulated pulse, then the echo signals received by multiple channels... The expression is as follows: ； in, This represents the scattering coefficient of the target. Indicates distance frequency modulation. Represents the speed of light. Indicates the wavelength of the transmitted signal. Indicates a fast time; S2. Perform range pulse compression and range migration correction on the echo data obtained in step S1; Set the matching function for pulse compression as follows: The signal after pulse compression The expression is as follows: ； Wherein, IFFT represents the inverse Fourier transform operator, and FFT represents the Fourier transform operator; Then, perform a range Fourier transform on equation (5) to obtain the echo signal in the range frequency domain. The expression is as follows: ； in, =FT[ ], Indicates the bandwidth of the LFM pulse. Indicates the carrier frequency. Indicates distance frequency; Then select the azimuth angle as °, slant distance is The point target is used as a reference target, and its coordinates are... The echo signal after phase compensation The expression is as follows: ； Then, the Keystone transform is used to implement the linear distance migration correction (RCM), which is a scaling transformation of slow time, as shown in the following expression: ； in, Indicates the slow time after scaling; Substituting equation (8) into equation (7) and performing an inverse Fourier transform of the distance, the echo after RCM is obtained. The expression is as follows: ； Then the echo of a range cell The expression is as follows: ； Then, in equation (10) Perform a Taylor expansion, retaining the first-order terms, as shown in the following expression: ； Finally, substituting equation (11) into equation (10), the echo of a range cell is obtained. The expression is as follows: ； The first term is a constant, the second term represents the path difference phase related to the spatial channel, and the third term represents the phase related to the synthetic aperture. S3. Based on the Doppler differences in different imaging regions, separate the echo data processed in step S2. The cutoff frequency is designed based on the critical angle, and then low-pass filtering is performed on each channel to separate the echoes along the track and those off the track. S4. Based on the echo data of different imaging regions obtained in step S3, different imaging schemes are executed, and the final imaging result is obtained by stitching together the imaging results of the two regions along the track and off the track. Among them, echoes along the flight path region are subjected to space-time super-resolution processing, while echoes deviating from the flight path region are subjected to space-time beamforming processing.

2. The efficient space-time processing method for multi-channel radar forward-looking imaging according to claim 1, characterized in that, Step S3 is as follows: According to equation (12), the approximate expressions for echo data in different regions within a single distance cell are as follows: ； ； in, , , as well as , , These represent the echo, scattering coefficient, and azimuth angle along the flight path and off the flight path, respectively. Design a low-pass filter to detect echoes. Extracting echoes along the flight path The cutoff frequency of a low-pass filter is the corresponding Doppler frequency. ; in, The critical angle represents the boundary between the deviation from the track area and the track area, determined based on the trend of angular resolution variation; and the angular resolution of multi-channel radar forward-looking imaging is expressed as the 3dB width of the angular ambiguity function. Therefore, according to equation (12), the angular ambiguity function of multi-channel radar forward-looking imaging... The expression is as follows: ； in, Indicates the azimuth of the target. This indicates the angular resolution of the multi-channel forward-looking SAR. Indicated Conjugate; Equation (15) is integrated to obtain the variation curve of the angular ambiguity function. Then, its 3dB variation range is truncated. The approximate expression of the angular resolution of the multi-channel forward-looking SAR is as follows: ； in, Indicates the synthetic aperture length. Indicates the actual aperture length; Then, the azimuth angle in equation (16) Find the partial derivative, the expression is as follows: ； Among them, the critical angle is determined when the value of equation (17) is less than the empirical threshold, with the system parameters fixed. Finally, the same low-pass filter was used on the echo data of each channel to obtain the echo data along the track area. Then, the echo data deviating from the track area is obtained by subtracting the echo data along the track area from the complete echo data. .

3. The efficient space-time processing method for multi-channel radar forward-looking imaging according to claim 2, characterized in that, Step S4 is as follows: First, the echoes of different regions corresponding to equations (13) and (14) are rewritten in discrete form, as shown in the following expressions: ； in, , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector, respectively, which deviate from the track area. , , and These represent the echo, steering matrix, scattering coefficient vector, and noise vector along the flight path region, respectively. Then guide matrix Represented as the Kronecker product of spatial and temporal vectors, the grid point vectors deviating from the flight path region are defined as follows: The specific expression for the guidance matrix is ​​as follows: ； in, , , , , Indicates the synthetic aperture sampling interval. The number of sampling points indicates the synthetic aperture. This indicates the number of antennas, i.e., the number of channels. Indicates the transpose operation; Similarly, the grid point vectors along the flight path region are... Substitute equation (19) to construct the corresponding guidance matrix. Then, for areas deviating from the flight path, space-time beamforming is introduced to achieve azimuth focusing for each range cell, as shown in the following expression: ； in, Indicates the imaging results, This represents the conjugate transpose operation; For the area along the flight path, an iterative optimization algorithm is used to enhance imaging performance. Specifically, for echo data of a certain range cell, an iterative adaptive algorithm is used to solve the constructed spatiotemporal linear observation equation. The specific calculation process is as follows: 1) Calculation ; 2) Calculate the covariance matrix ; 3) Update ; 4) Return to step 1). in, Represents the scattering coefficient matrix. Indicates the first Each scattering coefficient; This indicates the number of grid points divided along the flight path area. yes The Column vector, Represents the regularization parameter. Represents the identity matrix; After multiple iterations of steps 1)-4) to obtain converged results, the same operation is performed on the echo data of all range cells to obtain the imaging results along the track region. ; Finally, the final imaging result is obtained by stitching together the imaging results from the areas along the flight path and those deviating from the flight path.

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