MIMO-ArcSAR target detection method, electronic equipment and storage medium

Abstract

The invention discloses an MIMO-ArcSAR (Multiple Input Multiple Output-ArcSAR) target detection method, which is used for improving the target detection capability, expanding a single-channel ArcSAR system to a multi-channel system by combining an MIMO technology, and improving the signal-to-noise ratio of imaging by using a multi-channel coherent accumulation method so as to improve the detection probability. The MIMO-ArcSAR obtains an echo signal through arc scanning, and carries out range-direction matched filtering and azimuth-direction matched filtering on each channel to obtain a range-azimuth spectrum of a target. The method comprises the following steps: selecting a reference channel, constructing a multi-channel phase compensation item according to a geometrical relationship between multiple MIMO channels and the reference channel, compensating a received signal of each channel, performing coherent accumulation on a distance-azimuth spectrum of the multiple channels, improving the signal-to-noise ratio of an imaging result, and improving the detection probability and the detection distance of a target.

Description

Technical Field

[0001] The invention belongs to the technical field of radar signal processing, and in particular relates to a MIMO-ArcSAR target detection method, electronic equipment and storage medium. Background Art

[0002] Ground-based synthetic aperture radar (GB-SAR) is an important technology for remote sensing monitoring. Existing SAR systems achieve synthetic aperture by using two closely spaced horn antennas moving along a linear track. The radar transmits a linear frequency modulated continuous wave signal to the observation area and realizes scene imaging through the received echo. In order to obtain higher data acquisition efficiency and a wider viewing angle, the arc track-based synthetic aperture radar (ArcSAR) has been widely studied.

[0003] ArcSAR rotates in an arc trajectory, illuminates the observation area and receives echoes, and performs imaging through range-Doppler (RD) algorithm, back-projection algorithm (BP) algorithm and two-dimensional wavenumber domain algorithm. However, in the airport runway foreign object detection scenario, the target is seriously affected by ground clutter and noise, the single-channel imaging result is poor, and the effective range is limited, making it difficult to achieve target detection. In addition, most of the airport foreign objects are stationary targets and cannot be distinguished using Doppler information. Summary of the invention

[0004] The main purpose of the present invention is to provide a MIMO-ArcSAR target detection method, electronic equipment and storage medium to solve the problems existing in the prior art, realize the imaging and detection of weak targets and avoid missed detection.

[0005] In order to achieve the above object, the solution of the present invention is: A MIMO-ArcSAR target detection method, comprising: Step 1: MIMO-ArcSAR is equipped with N transmitting antennas and M receiving antennas, which transmit signals to the observation area while performing circular motion. for: ; in, Indicates fast time; represents the exponential function with the real number e as the base; represents an imaginary unit; Indicates carrier frequency; Indicates the frequency of FM; Step 2: The radar receives the target echo signal while making circular motion, and de-skews the echo signal to obtain a three-dimensional intermediate frequency echo signal. , and its calculation formula is: ; in, Indicates azimuth; Indicates MIMO virtual channels, Indicates transmitting antennas, Indicates receiving antennas; represents the azimuth dimension window function; represents the fast time window function; represents the speed of light; Indicates the target and The slant distance of the virtual channel; The calculation formula is: ; in, represents the distance from the target to the center of rotation, and the arm length is , the angle is ; The virtual channel transmitted by the first transmitting antenna and received by the first receiving antenna is taken as the reference channel, and its angle with the X-axis is , No. The angle between the virtual channel, the reference channel and the rotation center is , No. The angle between the virtual channel and the X-axis is ; Step 3: Perform two-dimensional focusing on the echo signal of each channel to obtain the range-azimuth imaging result ,in Indicates distance; Step 4: Calculate the slant range difference between the target and the reference channel and the remaining virtual channels. Taylor expansion is performed at, and the calculation formula is: ; Ignoring the higher-order terms above 2nd order, we get The slope distance difference between the virtual channel and the reference channel for: ; in , , considering the generality, use replace ; Step 5: Construct a phase compensation function based on the slant range difference. Phase compensation function for virtual channels The calculation formula is: ; Step 6: Compensate the phase of multiple channels and perform coherent accumulation to obtain the imaging result after coherent accumulation. , and its calculation formula is: ; Step 7: Perform constant false alarm detection on the imaging results after coherent accumulation to obtain the target's distance and azimuth estimation results.

[0006] An electronic device comprises a processor, a memory and an application program, wherein the application program is stored in the memory and is configured so that the processor executes the MIMO-ArcSAR target detection method.

[0007] A computer-readable storage medium stores a computer program, and when the computer program is executed in the computer, the computer executes the MIMO-ArcSAR target detection method.

[0008] After adopting the above technical solution, the present invention has the following technical effects: The present invention is based on MIMO-ArcSAR, obtains echo signals through arc scanning, performs range matching filtering and azimuth matching filtering on each channel respectively, and obtains the range-azimuth imaging result of the target; by selecting a reference channel, according to the geometric relationship between the MIMO multi-channel and the reference channel, calculates the slant range difference, constructs a multi-channel phase compensation term, and compensates and coherently accumulates the received signals of each channel respectively, thereby improving the signal-to-noise ratio of the imaging result; finally, constant false alarm detection is performed on the imaging result after coherent accumulation, and the range and azimuth estimation results of the target are obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 The figure is a flow chart of a method according to a specific embodiment of the present invention.

[0010] Figure 2 It is a schematic diagram of a MIMO-ArcSAR system according to a specific embodiment of the present invention.

[0011] Figure 3 This is an imaging scene diagram of a specific embodiment of the present invention.

[0012] Figure 4 This is a single-channel ArcSAR imaging result diagram of the existing technology.

[0013] Figure 5 This is a diagram of the coherent accumulation imaging result based on MIMO multi-channel phase compensation of the present invention.

[0014] Figure 6 This is an imaging result diagram of the non-coherent accumulation of the prior art. DETAILED DESCRIPTION

[0015] In order to further explain the technical solution of the present invention, the present invention is described in detail below through specific embodiments.

[0016] refer to Figure 1-2 As shown, the present invention discloses a MIMO-ArcSAR target detection method, comprising: Step 1: MIMO-ArcSAR is equipped with N transmitting antennas and M receiving antennas, which transmit signals to the observation area while performing circular motion. for: ; in, Indicates fast time; represents the exponential function with the real number e as the base; represents an imaginary unit; Indicates carrier frequency; Indicates the frequency of FM; Step 2: See Figure 1 The radar receives the target echo signal while making circular motion, and de-skews the echo signal to obtain a three-dimensional intermediate frequency echo signal. , and its calculation formula is: ; in, Indicates azimuth; Indicates MIMO virtual channels, Indicates transmitting antennas, Indicates receiving antennas; represents the azimuth dimension window function; represents the fast time window function; represents the speed of light; Indicates the target and The slant distance of the virtual channel; The calculation formula is: ; in, represents the distance from the target to the center of rotation, and the arm length is , the angle is ; The virtual channel transmitted by the first transmitting antenna and received by the first receiving antenna is taken as the reference channel, and its angle with the X-axis is , No. The angle between the virtual channel, the reference channel and the rotation center is , No. The angle between the virtual channel and the X-axis is ; Step 3: Perform two-dimensional focusing on the echo signal of each channel to obtain the range-azimuth imaging result ,in Indicates distance; Step 4: Calculate the slant range difference between the target and the reference channel and the remaining virtual channels. Taylor expansion is performed at, and the calculation formula is: ; Ignoring the higher-order terms above 2nd order, we get The slope distance difference between the virtual channel and the reference channel for: ; in , , considering the generality, use replace ; Step 5: Construct a phase compensation function based on the slant range difference. Phase compensation function for virtual channels The calculation formula is: ; Step 6: Compensate the phase of multiple channels and perform coherent accumulation to obtain the imaging result after coherent accumulation. , and its calculation formula is: ; Step 7: Perform constant false alarm detection on the imaging results after coherent accumulation to obtain the target's distance and azimuth estimation results.

[0017] Through the above scheme, the present invention is based on MIMO-ArcSAR, obtains echo signals through arc scanning, performs range matching filtering and azimuth matching filtering on each channel respectively, and obtains the range-azimuth imaging result of the target; by selecting a reference channel, according to the geometric relationship between the MIMO multi-channel and the reference channel, calculates the slant range difference, constructs a multi-channel phase compensation term, and compensates and coherently accumulates the received signals of each channel respectively, thereby improving the signal-to-noise ratio of the imaging result; finally, constant false alarm detection is performed on the imaging result after coherent accumulation, and the range and azimuth estimation results of the target are obtained.

[0018] In order to better illustrate the technical effect achieved by the present invention, the method of the present invention is experimentally compared with the existing method below; wherein, the radar system parameters are as follows:

[0019] The target parameters are as follows:

[0020] Figure 3 is the imaging scene graph of the present invention, Figure 4 This is the imaging result of single-channel ArcSAR. Figure 5 This is the coherent integration imaging result after multi-channel phase compensation. Figure 6 This is the non-coherent accumulation imaging result of multi-channels without phase compensation. Compared with the imaging result of single-channel ArcSAR, the present invention significantly improves the target signal-to-noise ratio: see Figure 4 , the target is seriously affected by ground clutter and noise, and the detection performance is poor; see Figure 6 The non-coherent integration method without phase compensation has no significant improvement on the target imaging quality; while the coherent integration method based on MIMO multi-channel phase compensation of the present invention (see Figure 5 ), the signal-to-noise ratio is significantly improved, which improves the detection performance.

[0021] The present invention also discloses an electronic device, comprising a processor, a memory and an application program; the application program is stored in the memory and is configured so that the processor executes the above-mentioned target detection method.

[0022] The present invention also discloses a computer-readable storage medium, which stores a computer program; when the computer program is executed in a computer, the computer executes the above-mentioned target detection method. The storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0023] The above embodiments and drawings do not limit the product form and style of the present invention. Any appropriate changes or modifications made by ordinary technicians in the relevant technical field should be deemed to be within the patent scope of the present invention.

Claims

1. A MIMO-ArcSAR target detection method, characterized in that include: Step 1: MIMO-ArcSAR is equipped with N transmitting antennas and M receiving antennas, which transmit signals to the observation area while performing circular motion. for: ； in, Indicates fast time; represents the exponential function with the real number e as the base; represents an imaginary unit; Indicates carrier frequency; Indicates the frequency of FM; Step 2: The radar receives the target echo signal while making circular motion, and de-skews the echo signal to obtain a three-dimensional intermediate frequency echo signal. , and its calculation formula is: ； in, Indicates azimuth; Indicates MIMO virtual channels, Indicates transmitting antennas, Indicates receiving antennas; represents the azimuth dimension window function; represents the fast time window function; represents the speed of light; Indicates the target and The slant distance of the virtual channel; The calculation formula is: ； in, represents the distance from the target to the center of rotation, and the arm length is , the angle is ; The virtual channel transmitted by the first transmitting antenna and received by the first receiving antenna is taken as the reference channel, and its angle with the X-axis is , No. The angle between the virtual channel, the reference channel and the rotation center is , No. The angle between the virtual channel and the X-axis is ; Step 3: Perform two-dimensional focusing on the echo signal of each channel to obtain the range-azimuth imaging result ,in Indicates distance; Step 4: Calculate the slant range difference between the target and the reference channel and the remaining virtual channels. Taylor expansion is performed at, and the calculation formula is: ； Ignoring the higher-order terms above 2nd order, we get The slope distance difference between the virtual channel and the reference channel for: ； in , , considering the generality, use replace ; Step 5: Construct a phase compensation function based on the slant range difference. Phase compensation function for virtual channels The calculation formula is: ； Step 6: Compensate the phase of multiple channels and perform coherent accumulation to obtain the imaging result after coherent accumulation. , and its calculation formula is: ； Step 7: Perform constant false alarm detection on the imaging results after coherent accumulation to obtain the target's distance and azimuth estimation results.

2. An electronic device comprising a processor, a memory and an application program, wherein the application program is stored in the memory, characterized in that The application is configured to execute the MIMO-ArcSAR target detection method according to claim 1 by the processor.

3. A computer-readable storage medium storing a computer program, characterized in that When the computer program is executed in the computer, the computer is caused to execute the MIMO-ArcSAR target detection method according to claim 1.

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