Fast backward projection method based on subaperture translation

Abstract

The invention provides a rapid backward projection method based on subaperture translation, and the method comprises the steps: constructing a three-dimensional coordinate system according to the moving track and sampling interval of a radar on a two-dimensional guide rail, and obtaining a radar coordinate; gridding processing is carried out on the imaging plane according to a back projection algorithm, and pixel point coordinates are obtained according to the distance between the radar sampling plane and the imaging plane; constructing a sliding matrix corresponding to the imaging matrix, calculating an initial distance matrix, and calculating a corresponding phase compensation matrix and a coefficient matrix according to the initial distance matrix; extracting a frequency domain signal amplitude of a corresponding distance point from the echo signal by using the coefficient matrix, and performing phase compensation on the echo signal by using the phase compensation matrix; and frequency domain signal amplitude extraction and phase compensation are carried out on all radar sampling points, and processed results are coherently superposed to an imaging matrix to obtain an imaging result. According to the invention, the final imaging quality can be ensured while the imaging efficiency is improved.

Description

Technical Field

[0001] The invention relates to the field of radar imaging technology, and in particular to a fast back-projection method based on sub-aperture translation. Background Art

[0002] Synthetic Aperture Radar (SAR) is a radar system with high-resolution imaging capabilities. It is widely used in target detection, environmental monitoring, disaster assessment and other fields because of its all-day and all-weather operation. Traditional SAR imaging algorithms, such as Range-Doppler algorithm, Chirp Scaling algorithm and ω-k algorithm, mainly rely on frequency domain processing technology and have high requirements for accurate modeling of slant range history. These algorithms have certain limitations when dealing with complex slant range changes and are difficult to meet imaging requirements in complex environments.

[0003] As a time-domain imaging algorithm, the back projection algorithm (BP) shows greater flexibility in processing complex slant range history by coherently superimposing echo signals. Compared with the frequency domain processing algorithm, the BP algorithm does not require complex modeling of slant range and can better adapt to the changing imaging environment. However, the traditional BP algorithm has a high computational complexity during the calculation process, especially when processing large-scale data or requiring real-time imaging. Since the algorithm needs to calculate the distance matrix frame by frame and perform coherent superposition, the imaging speed is slow and it is difficult to meet the requirements of real-time imaging.

[0004] In order to improve the imaging speed, a variety of improved back projection algorithms have been proposed in the prior art. For example, the Local Back Projection (LBP) algorithm, the Fast Back Projection (FBP) algorithm, and the Fast Factorized Back Projection (FFBP) algorithm. These algorithms can improve the imaging efficiency to a certain extent by introducing regional division, fast computing technology, and multi-level processing strategies. However, these improved algorithms still have some problems in the application process. For example, when imaging in a polar coordinate system, the image quality may be reduced due to the need for interpolation processing, and there is still a certain amount of computational redundancy.

[0005] In near-field synthetic aperture radar imaging, the distance between the radar and the imaging plane usually remains unchanged during the movement. This feature provides the possibility of simplifying the calculation process of the back-projection algorithm. When dealing with near-field imaging tasks, the traditional back-projection algorithm needs to repeatedly calculate the distance matrix for each frame of data, resulting in a large amount of computational redundancy, further reducing the overall imaging efficiency. Therefore, how to reduce the amount of calculation while maintaining the imaging quality has become an urgent problem to be solved in the existing technology. Summary of the invention

[0006] Based on this, it is necessary to provide a fast back-projection method based on sub-aperture translation to address the above technical problems.

[0007] A fast back projection method based on sub-aperture translation comprises the following steps: constructing a three-dimensional coordinate system according to the moving track and sampling interval of a radar on a two-dimensional guide rail to obtain radar coordinates; gridding the imaging plane according to a back projection algorithm, and obtaining pixel coordinates according to the distance between the radar sampling plane and the imaging plane; constructing a sliding matrix corresponding to an imaging matrix, calculating an initial distance matrix, and calculating a corresponding phase compensation matrix and a coefficient matrix according to the initial distance matrix; extracting the frequency domain signal amplitude of a corresponding distance point from an echo signal using the coefficient matrix, and performing phase compensation on the echo signal using the phase compensation matrix; performing frequency domain signal amplitude extraction and phase compensation on all radar sampling points, and coherently superimposing the processed results on the imaging matrix to obtain an imaging result.

[0008] In one embodiment, the three-dimensional coordinate system is constructed according to the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval to obtain the radar coordinates, including: the radar moves along the x-axis direction with d x The sampling is performed at intervals. After each line of scanning is completed, the y-axis moves d y The radar scans the next line in reverse. During the scanning process, the radar emits electromagnetic waves at each sampling point (x, y, 0) and receives echo signals. A three-dimensional coordinate system is constructed based on the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval. The radar coordinates are expressed as (x, y, 0) and the construction formula is:

[0009]

[0010] Where N x and N y are the number of sub-apertures of the radar on the X-axis and Y-axis, respectively, and d x and d y represent the spacing between subapertures on the X-axis and Y-axis respectively.

[0011] In one embodiment, the imaging surface is gridded according to the back-projection algorithm, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane. The formula is:

[0012]

[0013]

[0014] Where M x and M y is the number of pixels in the X-axis and Y-axis directions, pix represents the grid resolution, and the vertical distance between the imaging grid and the radar is z0, where d y and d y It is an integer multiple of pix to satisfy the coupling relationship of the sliding matrix.

[0015] In one embodiment, the calculation formula of the initial distance matrix is:

[0016]

[0017] In the formula, (x t ,y t ,z0) is the imaging grid coordinate.

[0018] In one embodiment, the calculation formula of the coefficient matrix is:

[0019]

[0020] In the formula, k s is the frequency modulation slope, Ts is the sampling interval, tI is the initial time, c is the speed of light, and nFFTtime is the number of FFT points.

[0021] In one embodiment, the calculation formula of the phase compensation matrix is:

[0022]

[0023] Among them, λ is the radar operating wavelength.

[0024] In one embodiment, the frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix. The formula is:

[0025]

[0026] In the formula, F back is the imaging matrix after coherent superposition.

[0027] Compared with the prior art, the advantages and beneficial effects of the present invention are as follows: a three-dimensional coordinate system is constructed according to the moving trajectory and sampling interval of the radar on the two-dimensional guide rail to obtain the radar coordinates. Through the constructed rectangular coordinate system, interpolation errors are avoided and imaging accuracy is improved; the imaging surface is gridded according to the back-projection algorithm, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane; a sliding matrix corresponding to the imaging matrix is ​​constructed, and the size of the sliding matrix is ​​adjusted to adapt to specific application requirements, and the imaging quality and imaging speed are flexibly balanced. The initial distance matrix is ​​calculated, and the corresponding phase compensation matrix and coefficient matrix are calculated according to the initial distance matrix, so that repeated calculations can be avoided by translating the distance matrix, thereby improving the imaging efficiency; the coefficient matrix is ​​used to extract the frequency domain signal amplitude of the corresponding distance point from the echo signal, and the phase compensation matrix is ​​used to perform phase compensation on the echo signal; the frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix to obtain the imaging result, so as to improve the imaging efficiency while ensuring the final imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a schematic flow chart of a fast back-projection method based on sub-aperture translation in one embodiment;

[0029] Figure 2 A schematic diagram of a millimeter wave radar scene setting in one embodiment;

[0030] Figure 3 A schematic diagram of a fast back-projection imaging algorithm based on sub-aperture translation in one embodiment;

[0031] Figure 4 A comparison diagram of multi-point simulation imaging of a fast back-projection imaging algorithm based on sub-aperture translation under different sliding matrix sizes in one embodiment;

[0032] Figure 5 A comparison diagram of single-point simulation imaging between a back-projection algorithm and a fast back-projection imaging algorithm based on sub-aperture translation in one embodiment;

[0033] Figure 6 This is a diagram showing the effect of a back-projection algorithm of measured data in one embodiment;

[0034] Figure 7 This is a diagram showing the effect of a fast back-projection imaging algorithm based on sub-aperture translation of measured data in one embodiment. DETAILED DESCRIPTION

[0035] Before describing the specific embodiments of the present invention, the overall concept of the present invention is described as follows:

[0036] The present invention is mainly developed based on the radar imaging process. At present, a large amount of repeated calculations are required in the imaging process of back-projection imaging, and the imaging efficiency is low. The existing efficiency improvement method will lead to a decrease in imaging quality.

[0037] Therefore, the present invention proposes a fast back-projection method based on sub-aperture translation, which constructs a three-dimensional coordinate system according to the moving trajectory and sampling interval of the radar on the two-dimensional guide rail to obtain the radar coordinates. Through the constructed rectangular coordinate system, interpolation errors are avoided and imaging accuracy is improved; the imaging surface is gridded according to the back-projection algorithm, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane; a sliding matrix corresponding to the imaging matrix is ​​constructed, and the size of the sliding matrix is ​​adjusted to adapt to specific application requirements, and the imaging quality and imaging speed are flexibly balanced. The initial distance matrix is ​​calculated, and the corresponding phase compensation matrix and coefficient matrix are calculated according to the initial distance matrix, so that repeated calculations can be avoided by translating the distance matrix to improve the imaging efficiency; the coefficient matrix is ​​used to extract the frequency domain signal amplitude of the corresponding distance point from the echo signal, and the phase compensation matrix is ​​used to perform phase compensation on the echo signal; the frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix to obtain the imaging result, so as to improve the imaging efficiency while ensuring the final imaging quality.

[0038] After introducing the overall concept of the present invention, in order to make the purpose, technical solution and advantages of the present invention more clear, the present invention is further described in detail by specific implementation methods in combination with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0039] In one embodiment, Figure 1 As shown, a fast back-projection method based on sub-aperture translation is provided, comprising the following steps:

[0040] Step S110, constructing a three-dimensional coordinate system according to the movement trajectory of the radar on the two-dimensional guide rail and the sampling interval to obtain the radar coordinates.

[0041] Specifically, a 77-81GHz millimeter-wave radar is used, mounted on a high-precision cross slide, to scan the target, and high-precision MIMO-SAR imaging is performed through fast back-projection imaging based on sub-aperture translation. A three-dimensional rectangular coordinate system is constructed based on the movement trajectory and sampling interval of the radar on the two-dimensional guide rail, and the corresponding radar coordinates are obtained based on the constructed three-dimensional coordinate system. The constructed coordinate system facilitates subsequent calculations, avoids interpolation calculations and errors in the polar coordinate system, and improves imaging accuracy.

[0042] Wherein, step S110 includes: the radar moves along the x-axis direction at d xThe sampling is performed at intervals. After each line of scanning is completed, the y-axis moves d y The radar scans the next line in reverse. During the scanning process, the radar emits electromagnetic waves at each sampling point (x, y, 0) and receives echo signals. A three-dimensional coordinate system is constructed based on the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval. The radar coordinates are expressed as (x, y, 0) and the construction formula is:

[0043]

[0044] Where N x and N y are the number of sub-apertures of the radar on the X-axis and Y-axis, respectively, and d x and d y represent the spacing between subapertures on the X-axis and Y-axis respectively.

[0045] Specifically, the millimeter wave radar moves in the xy plane, and the coordinates of the radar are expressed as (x, y, 0). The radar moves along the x-axis at a speed of d x The sampling is performed at intervals. After each line of scanning is completed, the y-axis moves d y The distance is then scanned in reverse for the next line. During the scanning process, the radar transmits electromagnetic waves at each sampling point (x, y, 0) and receives echo signals. The above sampling points constitute the scanning trajectory, such as Figure 2 shown.

[0046] like Figure 2 In the radar scenario shown, the radar transmits and receives a frequency modulated continuous wave (FMCW) at a sampling point. Since the radar movement speed is negligible compared to the radar signal speed, the radar sampling point can be equivalent to a stationary state.

[0047] The frequency modulated continuous wave signal is expressed as:

[0048]

[0049] In the formula, A is the amplitude of the transmitted signal, K is the frequency modulation slope, and the calculation formula is K = B / T, where B is the frequency sweep bandwidth and T is the entire signal transmission time. Therefore, the phase of the transmitted signal is expressed as:

[0050]

[0051] There is a target at the radar's normal distance R, denoted as P. The echo signal of the point target P is expressed as:

[0052] S r (t)=δAexp(j2π(f0(t-τ)+K(t-τ) 2 / 2)+φ),t∈[0,T];

[0053] Where δ is the signal attenuation amplitude, τ is the time delay between the antenna receiving signal and the transmitting signal, τ = 2R / c, and the phase of the received signal is expressed as:

[0054]

[0055] By mixing the received echo signal with the transmitted signal and then using a low-pass filter to filter out the high-frequency useless signal generated by the mixer, a single-frequency signal representing the target point can be obtained, namely the intermediate frequency signal, which appears as a pulse in the frequency domain. According to the above formula, the intermediate frequency signal is:

[0056] S(t)=σexp(-j2π(f0+Kτt-0.5Sτ 2 )),0≤t≤T;

[0057] Where Kτ is the signal frequency and the calculation formula is:

[0058] f m = Kτ;

[0059] After collecting the intermediate frequency signal frequency f m After that, since the intermediate frequency signal frequency is the difference between the transmission signal frequency and the received signal frequency, and the signal transmitted by the radar is a frequency modulated continuous wave, the signal frequency changes linearly with time. Therefore, the signal round-trip delay can be calculated based on the intermediate frequency signal and the frequency modulation slope, and then the distance between the transmission point and the radar signal transmission point can be calculated by the electromagnetic wave propagation speed. The calculation formula is:

[0060]

[0061] Therefore, the full aperture echo signal can be expressed as a two-dimensional matrix S(t), which is:

[0062]

[0063] Step S120, gridding the imaging plane according to the back-projection algorithm, and obtaining pixel coordinates according to the distance between the radar sampling plane and the imaging plane.

[0064] Specifically, the imaging plane is gridded by a back-projection algorithm, and the pixel coordinates are obtained in a three-dimensional rectangular coordinate system according to the distance between the radar plane and the imaging plane, so as to facilitate subsequent calculations according to the three-dimensional rectangular coordinate system, avoid interpolation calculations and errors in the polar coordinate system, and improve imaging accuracy.

[0065] Among them, the formula for constructing pixel coordinates is:

[0066]

[0067] Where M x and M y is the number of pixels in the X-axis and Y-axis directions, pix represents the grid resolution, and the vertical distance between the imaging grid and the radar is z0, where d y and d y It is an integer multiple of pix to satisfy the coupling relationship of the sliding matrix.

[0068] Specifically, an imaging grid is established on the z=z0 plane, and the grid point coordinates (x t ,y t ,z0) to construct and obtain the pixel coordinates.

[0069] Step S130, constructing a sliding matrix corresponding to the imaging matrix, calculating an initial distance matrix, and calculating a corresponding phase compensation matrix and coefficient matrix according to the initial distance matrix.

[0070] Specifically, a sliding matrix corresponding to the imaging matrix is ​​constructed, the initial distance matrix is ​​calculated, and the corresponding phase compensation matrix and coefficient matrix are calculated based on the initial distance matrix. The sliding matrix is ​​used to translate the distance matrix, which reduces repeated calculations, and can significantly improve efficiency, especially when performing large-scale sub-aperture and high-resolution imaging. By adjusting the size of the sliding matrix, the imaging quality and imaging speed can be flexibly balanced according to specific application requirements.

[0071] like Figure 3 As shown, the sliding matrix uses the same distance matrix to reduce the amount of calculation by sliding to different radar coordinates. Therefore, it is necessary to construct a distance matrix that is applicable to all sub-apertures, construct an initial distance matrix, and translate through the distance matrix to reduce repeated calculations and improve imaging efficiency.

[0072] During the calculation process, there is no need to calculate the distance matrix for each radar sampling point. The distance matrix is ​​calculated once and then slid to the coordinates of each radar sampling point to remove the calculation redundancy of the distance matrix. The larger the sliding matrix, the better the imaging quality.

[0073] The back-projection algorithm requires coherent addition of the echo data and the frequency points corresponding to the initial distance matrix. Therefore, it is necessary to calculate the coefficient matrix corresponding to the initial distance matrix.

[0074] During the calculation process, it is not necessary to calculate the phase compensation for each radar sampling point separately, because the phase compensation matrix can be calculated by using the same distance matrix.

[0075] On the one hand, the movement of the platform causes the range dimension to undergo range migration, that is, the distances of the same grid points at different azimuths (slow time) are different; on the other hand, the movement of the platform causes the pulse echo of the same target at different azimuths and times to be superimposed with a Doppler signal caused by instantaneous distance transformation. Since each pulse time is very short, the Doppler effect in fast time is generally not considered. The time interval of slow time is larger, and the Doppler effect cannot be ignored. At this time, the Doppler effect in slow time (azimuth) is reflected on the distance curve. In order to achieve pulse compression in the azimuth dimension, it is necessary to compensate the corresponding Doppler phase along the distance prior curve to achieve pulse compression in the azimuth dimension. The compensated Doppler phase is obtained by obtaining the phase compensation matrix from the precise slant range information. In this step, the imaging speed and imaging quality can be changed by modifying the sliding matrix size. The comparison of imaging quality under different sliding matrix sizes is shown in Figure 2. Figure 4 shown.

[0076] Among them, the calculation formula of the initial distance matrix is:

[0077]

[0078] In the formula, (x t ,y t ,z0) is the imaging grid coordinate.

[0079] Among them, the calculation formula of the coefficient matrix is:

[0080]

[0081] In the formula, k s is the frequency modulation slope, Ts is the sampling interval, tI is the initial time, c is the speed of light, and nFFTtime is the number of FFT points.

[0082] Among them, the calculation formula of the phase compensation matrix is:

[0083]

[0084] Where λ is the radar operating wavelength.

[0085] Step S140: extract the frequency domain signal amplitude of the corresponding distance point from the echo signal using the coefficient matrix, and perform phase compensation on the echo signal using the phase compensation matrix.

[0086] Specifically, a coefficient matrix is ​​used to extract the frequency domain signal amplitude of the corresponding distance point from the radar echo signal, and a phase compensation matrix is ​​used to perform phase compensation on the echo signal.

[0087] Step S150, frequency domain signal amplitude extraction and phase compensation are performed on the radar sampling points, and the processed results are coherently superimposed on the imaging matrix to obtain an imaging result.

[0088] Specifically, step S140 is repeatedly performed for each radar sampling point to perform frequency domain signal amplitude extraction and phase compensation to obtain corresponding results, and the results are coherently added to the imaging matrix to obtain imaging results. Through the above steps, a better noise suppression effect is obtained, and the final imaging quality is improved.

[0089] Among them, the calculation formula of the imaging matrix is:

[0090]

[0091] In the formula, F back is the imaging matrix after coherent superposition.

[0092] In this embodiment, a three-dimensional coordinate system is constructed according to the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval to obtain the radar coordinates. The interpolation error is avoided and the imaging accuracy is improved by the constructed rectangular coordinate system; the imaging surface is gridded according to the back-projection algorithm, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane; a sliding matrix corresponding to the imaging matrix is ​​constructed, and the size of the sliding matrix is ​​adjusted to adapt to specific application requirements, and the imaging quality and imaging speed are flexibly balanced. The initial distance matrix is ​​calculated, and the corresponding phase compensation matrix and coefficient matrix are calculated according to the initial distance matrix, so that repeated calculations can be avoided by translating the distance matrix to improve the imaging efficiency; the frequency domain signal amplitude of the corresponding distance point is extracted from the echo signal by using the coefficient matrix, and the phase compensation matrix is ​​used to perform phase compensation on the echo signal; the frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix to obtain the imaging result, achieving a better noise suppression effect, while improving the imaging efficiency and ensuring the final imaging quality.

[0093] like Figure 5 As shown in the figure, it is a comparison diagram of single-point simulation imaging of the back-projection algorithm and the fast back-projection imaging algorithm based on sub-aperture translation. It can be seen from the image that the back-projection algorithm and the fast back-projection imaging algorithm based on sub-aperture translation have similar imaging quality. Since the back-projection algorithm uses the full aperture for imaging during the imaging process, the imaging resolution is slightly higher, and the energy is more concentrated in the central area. At the same time, the imaging noise is mainly distributed at the edge of the image. The contour map generated by the fast back-projection imaging algorithm based on sub-aperture translation and the energy focusing degree and imaging details in the central area of ​​the imaging result are basically consistent with the back-projection algorithm, and the target details can still be well imaged.

[0094] In addition, since each sub-aperture performs reverse projection directly on the imaging grid during projection calculation in the fast back-projection imaging algorithm based on sub-aperture translation, the imaging noise distribution is more uniform and the noise suppression is more outstanding. In terms of imaging contrast, although the energy diffusion of the fast back-projection imaging algorithm based on sub-aperture translation is slightly obvious, it does not affect the imaging clarity. The imaging time of the two algorithms at different imaging resolutions and aperture numbers is shown in Table 1.

[0095] Table 1 Imaging time under different sliding matrix sizes

[0096]

[0097] It can be seen from Table 1 that at all image resolutions and aperture numbers, the imaging speed of the algorithm of the present invention is significantly better than that of the existing back-projection algorithm. 2 The time consumption of the two algorithms is mainly concentrated in the coherent superposition part, and the calculation time difference is not large when traversing different frequency points during simulation calculation; when the number of sub-apertures and imaging resolution is larger, such as 500 2 The time consumption of the two algorithms differs by more than ten times, and the efficiency of the algorithm of the present invention is more significant.

[0098] like Figure 6 and Figure 7 The results of imaging with two algorithms using measured data are shown in Figure 2. Comparing the imaging results, it can be clearly seen that compared with the back-projection algorithm, the fast back-projection imaging algorithm based on sub-aperture translation effectively suppresses noise and reduces artifacts, especially at the edges and details of the image, significantly improving the blur problem; and the fast back-projection imaging algorithm based on sub-aperture translation takes 11.97 seconds, while the back-projection algorithm takes 78.39 seconds, greatly reducing the imaging time.

[0099] In summary, the present invention uses the characteristic that the distance between the radar and the imaging plane remains unchanged during the near-field imaging process, and no longer repeatedly calculates the distance matrix each time, but uses the same distance matrix for calculation each time, thereby eliminating the computational redundancy of the traditional back-projection algorithm in near-field imaging and greatly improving the imaging efficiency. Another advantage of using a sliding matrix for projection imaging is that the image quality and imaging speed can be easily balanced by adjusting the matrix size. In addition, the present invention performs imaging in a rectangular coordinate system, and compared with FFBP in a traditional polar coordinate system, there is no need to repeatedly perform interpolation calculations, thereby avoiding calculation errors caused by interpolation.

[0100] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0101] Obviously, those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a computer storage medium (ROM / RAM, magnetic disk, optical disk) and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order than that here, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Therefore, the present invention is not limited to any specific combination of hardware and software.

[0102] The above contents are further detailed descriptions of the present invention in combination with specific implementation methods, and it cannot be determined that the specific implementation of the present invention is limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the scope of protection of the present invention.

Claims

1. A fast backprojection method based on subaperture translation, characterized in that: The following steps are involved: A three-dimensional coordinate system is constructed according to the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval to obtain the radar coordinates; The imaging plane is gridded according to the back-projection algorithm, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane; Constructing a sliding matrix corresponding to the imaging matrix, calculating an initial distance matrix, and calculating a corresponding phase compensation matrix and a coefficient matrix according to the initial distance matrix; The coefficient matrix is ​​used to extract the frequency domain signal amplitude of the corresponding distance point from the echo signal, and the phase compensation matrix is ​​used to perform phase compensation on the echo signal; The frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix to obtain the imaging result.

2. The fast back-projection method based on sub-aperture translation according to claim 1, characterized in that: The process of constructing a three-dimensional coordinate system according to the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval to obtain the radar coordinates includes: The radar is moving along the x-axis at d x The sampling is performed at intervals. After each line of scanning is completed, the y-axis moves d y The radar transmits electromagnetic waves at each sampling point (x, y, 0) and receives echo signals. A three-dimensional coordinate system is constructed based on the moving trajectory of the radar on the two-dimensional guide rail and the sampling interval. The radar coordinates are expressed as (x, y, 0) and the construction formula is: Where N x and N y are the number of sub-apertures of the radar on the X-axis and Y-axis, respectively, and d x and d y represent the spacing between subapertures on the X-axis and Y-axis respectively.

3. The fast back-projection method based on sub-aperture translation according to claim 2, characterized in that: According to the back-projection algorithm, the imaging surface is gridded, and the pixel coordinates are obtained according to the distance between the radar sampling plane and the imaging plane. The formula is: Where M x and M y is the number of pixels in the X-axis and Y-axis directions, pix represents the grid resolution, and the vertical distance between the imaging grid and the radar is z0, where d y and d y It is an integer multiple of pix to satisfy the coupling relationship of the sliding matrix.

4. The fast back-projection method based on sub-aperture translation according to claim 3, characterized in that: The calculation formula of the initial distance matrix is: In the formula, (x t ,y t ,z0) is the imaging grid coordinate.

5. The fast back-projection method based on sub-aperture translation according to claim 4, characterized in that: The calculation formula of the coefficient matrix is: In the formula, k s is the frequency modulation slope, Ts is the sampling interval, tI is the initial time, c is the speed of light, and nFFTtime is the number of FFT points.

6. The fast back-projection method based on sub-aperture translation according to claim 5, characterized in that: The calculation formula of the phase compensation matrix is: Among them, λ is the radar operating wavelength.

7. The fast back-projection method based on sub-aperture translation according to claim 6, characterized in that: The frequency domain signal amplitude extraction and phase compensation are performed on all radar sampling points, and the processed results are coherently superimposed on the imaging matrix. The formula is: In the formula, F back is the imaging matrix after coherent superposition.

Images