A Fast Time-Domain Imaging Method for Arc Synthetic Aperture Imaging

Abstract

The present invention relates to the technical field of radar fast imaging algorithms, and specifically to a fast time-domain imaging algorithm for arc-shaped synthetic aperture imaging. The algorithm mainly comprises the following steps: S1, establishing a model; S2, calculating a single-beam matching function; and S3, performing imaging calculation. Aiming at the fast and high-precision imaging requirements of arc-shaped deformation monitoring radars, the present invention combines an arc-shaped synthetic aperture imaging radar system and proposes a fast time-domain imaging algorithm. While ensuring high-precision imaging, the algorithm greatly reduces the amount of computation, thereby meeting the system's requirements for imaging accuracy and imaging speed.

Description

Technical Field

[0001] The present invention relates to the technical field of radar fast imaging algorithms, in particular to a fast time-domain imaging method for arc-shaped synthetic aperture imaging. Background Art

[0002] my country is one of the countries in the world with the most serious geological disasters and the largest threatened population. Among them, landslide disasters are the most frequent and most harmful geological disasters. In recent years, slope deformation monitoring radar has developed rapidly in the field of landslide disaster prevention and control due to its high measurement accuracy, all-day, all-weather and continuous detection. At present, many research institutions at home and abroad have carried out research on slope deformation monitoring radar.

[0003] Currently, most slope deformation monitoring radars, both domestically and internationally, are based on the principle of synthetic aperture imaging. They can be categorized by radar architecture into sliding-track, MIMO, and rotary types. The first two types rely on linear array scanning, which, due to limited scanning length, limits both observation range and resolution. Rotating synthetic aperture radars, however, utilize a rotating robotic arm to achieve a wider observation range and superior resolution with the same hardware length. For example, patent CN 109917386A describes a rotating ground-based interferometric synthetic aperture radar system. The algorithm described in this proposal is applicable to similar systems.

[0004] In order to realize the high-precision deformation monitoring function of the rotary deformation monitoring radar, we must first approach the problem of fast and high-resolution imaging, that is, we need to meet both high resolution and fast imaging requirements. Since the synthetic aperture is changed from a linear array to an arc array, the use of classic synthetic aperture imaging algorithms will face problems such as decreased accuracy or excessive computational complexity, which will directly affect the system's refresh rate and deformation speed monitoring range. Summary of the Invention

[0005] The purpose of the present invention is to provide a fast time-domain imaging method for arc-shaped synthetic aperture imaging, so as to solve the technical problems that current synthetic aperture imaging algorithms are mostly based on linear scanning models. When applied to circular arc synthetic aperture systems, frequency domain algorithms are prone to imaging quality degradation due to mismatch, and time domain algorithms need to calculate the distance from each sampling point to each imaging point, which results in excessive computational complexity and cannot meet the image refresh rate requirements.

[0006] The object of the present invention is achieved by the following technical solution: a fast time-domain imaging method for arc-shaped synthetic aperture imaging, comprising the following steps:

[0007] S1. Build the model;

[0008] S2, calculating the single beam matching function;

[0009] S3, imaging calculation;

[0010] Wherein, in said S1, establishing the model specifically includes the following steps:

[0011] S10. Establish a polar coordinate system with the radar axis as the center, and set the initial pointing angle of the radar axis to 0°. The radar moves at a constant speed around the origin with a rotation radius of L. The coordinates of each sampling point are ( , ), and the imaging range is the circular area centered on the origin, and the imaging radius range is (R1, R2), R1>L;

[0012] S11. Select sampling and imaging angle intervals ;

[0013] S12, select imaging distance interval .

[0014] It should be noted here that, in response to the fast and high-precision imaging requirements of the arc-type deformation monitoring radar, the applicant has proposed a fast time-domain imaging algorithm based on the arc-type synthetic aperture imaging radar system. While ensuring high-precision imaging, it greatly reduces the amount of computation to meet the system's requirements for imaging accuracy and imaging speed.

[0015] Furthermore, in said S11, the sampling and imaging angle intervals are selected include:

[0016] Calculation of azimuth resolution: Assuming the system transmits a linear frequency modulation signal with a center frequency of f0, a bandwidth of B, and a modulation frequency of K, the azimuth resolution can be calculated using the following formula:

[0017] (1)

[0018] in is the azimuth resolution in degrees, is the wavelength, L is the radius of rotation, is the antenna beam width;

[0019] Angle interval Should not be greater than the azimuth resolution , and try to take a larger value; angle interval It should be divisible by 360; then the number of azimuth points N for sampling and imaging a single image (360°) is: ;

[0020] Number of azimuth points for single beamwidth (θ) sampling and imaging for: .

[0021] Furthermore, in said S12, the imaging distance interval is selected include:

[0022] Calculate the imaging distance resolution, the expression is:

[0023] (2)

[0024] in, is the distance resolution in meters, c is the speed of light, and B is the bandwidth of the transmitted signal;

[0025] The imaging distance interval Should not be greater than the distance resolution , then the number of distance points of a single image is M=[R2-R1 / ] .

[0026] Furthermore, in said S2, calculating the single beam matching function includes: calculating the distance of the chirp signal after compression and calculating the single sampling point matching function;

[0027] The expression for calculating the distance of the compressed chirp signal is:

[0028] (3)

[0029] is the envelope of the distance compression result, R is the distance to the target, is the wavelength of the transmitted signal, K is the modulation frequency;

[0030] In addition, the expression for calculating the single sampling point matching function is:

[0031] (4)

[0032]

[0033]

[0034] (5)

[0035] Furthermore, in S3, the imaging calculation includes:

[0036] S30, single sampling point BP back projection, the expression is:

[0037] (6)

[0038] Where, m=1,2,…,M; n=1,2,…,N0;

[0039] S31, imaging result initialization; the imaging result of the qth track initialization is as follows:

[0040] (7)

[0041] S32, accumulation of imaging results; the accumulation of imaging results of the qth track is calculated as follows:

[0042] (8)

[0043] S33, imaging result extraction:

[0044] (9)

[0045] It should be noted here that in S32 and S33, The definition is the same as S30, that is, m=1,…,M, n=1,…, .

[0046] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0047] Aiming at the fast and high-precision imaging requirements of arc-type deformation monitoring radar, the present invention proposes a fast time-domain imaging algorithm in combination with an arc-type synthetic aperture imaging radar system. While ensuring high-precision imaging, the algorithm greatly reduces the amount of computation to meet the system's requirements for imaging accuracy and speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 It is a schematic diagram of the process steps of the present invention. DETAILED DESCRIPTION

[0049] Please refer to the attached instructions Figure 1 This embodiment provides a fast time-domain imaging method for arc-shaped synthetic aperture imaging. This algorithm is mainly used to solve the problem in the existing technology that the synthetic aperture is changed from a linear array to an arc array, and the use of the classic synthetic aperture imaging algorithm will face the problem of reduced accuracy or excessive computational complexity, which will directly affect the system's refresh rate and deformation speed monitoring range.

[0050] It should be noted that the entire process of this scheme is mainly divided into three processing steps: the first step is to calculate the model parameters, including establishing the model, selecting the azimuth and range imaging grids, and calculating the number of azimuth and range processing points; the second step is to calculate the single-beam matching function at one time, that is, the backprojection matching function of a single sampling point within the beam range; the third step is to cyclically execute the imaging calculation, cyclically execute the single-point backprojection and the superposition of the imaging results, where the matching function of each single-point backprojection is the single-beam matching function obtained in step 2.

[0051] The specific implementation steps are as follows:

[0052] S1. Establishing a model; establishing a model specifically includes the following steps:

[0053] S10. Establish a polar coordinate system with the radar axis as the center, set the initial pointing angle of the radar axis to 0°, and the radar moves at a constant speed around the origin with a rotation radius of L. Then the coordinates of each sampling point are ( , ), and the imaging range is the circular area centered on the origin, and the imaging radius range is (R1, R2), R1>L;

[0054] S11. Select sampling and imaging angle intervals ,include:

[0055] Calculation of azimuth resolution: Assuming the system transmits a linear frequency modulation signal with a center frequency of f0, a bandwidth of B, and a modulation frequency of K, the azimuth resolution can be calculated using the following formula:

[0056] (1)

[0057] in is the azimuth resolution in degrees, is the wavelength, L is the radius of rotation, is the antenna beam width;

[0058] Angle interval Should not be greater than the azimuth resolution , and try to take a larger value; angle interval It should be divisible by 360; then the number of azimuth points N for sampling and imaging a single image (360°) is: ;

[0059] Number of azimuth points for single beamwidth (θ) sampling and imaging for: ;

[0060] S12, select imaging distance interval ,include:

[0061] Calculate the imaging distance resolution, the expression is:

[0062] (2)

[0063] in, is the distance resolution in meters, c is the speed of light, and B is the bandwidth of the transmitted signal;

[0064] The imaging distance interval Should not be greater than the distance resolution , then the number of distance points of a single image is M=[R2-R1 / ] ;

[0065] S2. Calculating a single-beam matching function, including calculating the distance of the compressed chirp signal and calculating a single-sampling point matching function;

[0066] The expression for calculating the distance of the compressed chirp signal is:

[0067] (3)

[0068] is the envelope of the distance compression result, R is the distance to the target, is the wavelength of the transmitted signal, K is the modulation frequency;

[0069] In addition, the expression for calculating the single sampling point matching function is:

[0070] (4)

[0071]

[0072]

[0073] (5)

[0074] S3, imaging calculation, mainly includes:

[0075] S30, single sampling point BP back projection, the expression is:

[0076] (6)

[0077] Where, m=1,2,…,M; n=1,2,…,N0;

[0078] S31, imaging result initialization; the imaging result of the qth track initialization is as follows:

[0079] (7)

[0080] S32, accumulation of imaging results; the accumulation of imaging results of the qth track is calculated as follows:

[0081] (8)

[0082] S33, imaging result extraction:

[0083] (9)

[0084] It should be noted here that in S32 and S33, The definition is the same as S30, that is, m=1,…,M, n=1,…, .

[0085] The effectiveness of the algorithm of the present invention is verified by actual measured data.

[0086] In the test scenario, the system parameters are shown in the following table.

[0087] Signal frequency range (GHz) 15-17 Signal bandwidth (MHz) 600 Azimuth coverage angle (°) 360 Imaging distance range (m) 50-200 Repetition rate (kHz) 1.25 Antenna azimuth beamwidth (°) 100° Radar rotation radius (m) 0.825 Sampling rotation speed (° / s) 3

[0088] An angular reflection target is placed in the imaging scene, and the angular reflection target is located about 100 meters away from the radar. Imaging calculation is performed according to the method.

[0089] First, calculate the azimuth resolution If the sampling and imaging azimuth interval is 0.4°, the sampling and imaging azimuth interval can be set to 0.3°, and the number of azimuth points N for a single image is 1200; the number of azimuth points N0 for a single beam is 334. According to the method, the distance resolution is calculated to be 0.25m, and the distance imaging interval can be selected is 0.2m, so the number of imaging distance points M is 750.

[0090] After that, perform steps 2 and 3 to achieve rapid imaging.

[0091] The fast algorithm of this scheme is accelerated mainly in two aspects: (1) In the classic BP algorithm, the matching function needs to be calculated for each sampling point according to the following formula: , for the system parameters of the example, it is necessary to perform N*N0*M matching function operations, while this scheme only needs to perform N0*M operations without using approximate methods to reduce the resolution, which can greatly reduce the amount of calculation; (2) For the synthetic aperture imaging system, in order to achieve the optimal resolution, each pixel point needs to be fully accumulated and imaged, that is, if you want to achieve the optimal resolution imaging in the 360-degree range, a single track needs to collect and process 360+100 degrees of data. When using this method for continuous acquisition operations, the intermediate accumulation result of the previous track data can be directly used for the next track operation. Therefore, only 360° data needs to be continuously collected to achieve complete accumulation imaging in the 360° range, simplifying the operation.

[0092] In summary, in the example described in this article, the imaging time can be reduced to about 1 / 7 compared with the classic BP algorithm.

[0093] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A fast time-domain imaging method for arc-shaped synthetic aperture imaging, characterized in that: The following steps are involved: S1. Build the model; S2, calculating the single beam matching function; S3, imaging calculation; Wherein, in said S1, establishing the model specifically includes the following steps: S10. Establish a polar coordinate system with the radar axis as the center, set the initial pointing angle of the radar axis to 0°, and the radar moves at a constant speed around the origin with a rotation radius of L. Then the coordinates of each sampling point are ( , ), and the imaging range is the circular area centered on the origin, and the imaging radius range is (R1, R2), R1>L; S11. Select sampling and imaging angle intervals ; S12, select imaging distance interval ; In said S2, calculating the single beam matching function includes: calculating the distance of the chirp signal after compression and calculating the single sampling point matching function; The expression for calculating the distance of the compressed chirp signal is: （3） is the envelope of the distance compression result, R is the distance to the target, is the wavelength of the transmitted signal, K is the modulation frequency; In addition, the expression for calculating the single sampling point matching function is: （4） ； ； ； （5） In S3, the imaging calculation includes: S30, single sampling point BP back projection, the expression is: （6） Where m=1,2,…,M; n=1,2,…, ; S31, imaging result initialization; the imaging result of the qth track initialization is as follows: （7） S32, accumulation of imaging results; the accumulation of imaging results of the qth track is calculated as follows: （8） S33, imaging result extraction: （9） It should be noted here that in S32 and S33, The definition is the same as S30, that is, m=1,…,M, n=1,…, .

2. The arc-shaped synthetic aperture imaging fast time-domain imaging method according to claim 1, characterized in that: In said S11, the sampling and imaging angle intervals are selected include: Calculation of azimuth resolution: Assuming the system transmits a linear frequency modulation signal with a center frequency of f0, a bandwidth of B, and a modulation frequency of K, the azimuth resolution can be calculated using the following formula: （1） in is the azimuth resolution in degrees, is the wavelength, L is the radius of rotation, is the antenna beam width; Angle interval Should not be greater than the azimuth resolution , and try to take a larger value; angle interval It should be divisible by 360; then the number of azimuth points N for sampling and imaging a single image is: ; Number of azimuth points for single beamwidth sampling and imaging for: .

3. The arc-shaped synthetic aperture imaging fast time-domain imaging method according to claim 1, characterized in that: In the step S12, the imaging distance interval is selected. include: Calculate the imaging distance resolution, the expression is: （2） in, is the distance resolution in meters, c is the speed of light, and B is the bandwidth of the transmitted signal; The imaging distance interval Should not be greater than the distance resolution , then the number of distance points of a single image is M=[R2-R1 / ].

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