Corner reflector array design method based on scattering center extraction

Abstract

The invention discloses a corner reflector array design method based on scattering center extraction, and the method carries out the research and analysis of the electromagnetic scattering characteristics of a metal target in a complex scene, provides a feasible scheme for the electromagnetic concealment of an important target, and specifically comprises the steps: extracting an attribute scattering center model of the target according to a radar echo; the coordinate parameters are used for initial arrangement of a corner reflector array; optimizing the corner reflector array by taking the structural similarity as a target function, and taking the optimized corner reflector array as a quality evaluation index of the arrangement of the corner reflector array; and finally obtaining a false target which is constructed by the corner reflector array and is similar to the target scattering characteristic. According to the method, the target concealment performance of corner reflector array arrangement in a complex scene is 90% or above, and compared with a radar image of a target, the method has high similarity.

Description

Technical Field

[0001] The invention belongs to the field of radar echo detection, in particular to a corner reflector array design method based on scattering center extraction. Background Art

[0002] Corner reflectors are mature and reliable passive jamming devices. Due to their special structure, they can generate strong echo signals in the direction of radar illumination, simulating the radar scattering characteristics of targets that are much larger than their own size. They can interfere with and deceive the terminal guidance radar of anti-ship missiles. For radars with high-resolution range imaging capabilities, a single corner reflector is limited by its own size and incident angle, making it difficult to meet the requirements of the jamming function. Ships are often detected as extended targets, so they are usually deployed in the form of an array of multiple corner reflectors, which can simulate the target and play an important role in protecting the target.

[0003] The method proposed in the present invention uses the scattering center coordinates and attitude angles extracted from the attribute scattering center as the initial solution for the corner reflector array arrangement, and uses the array optimization algorithm to calculate the structural similarity between the corner reflector array and the target's radar image, thus overcoming the difficulty in generating radar images and being able to design corresponding corner reflector arrays for different targets. Ship corner reflector decoys came into being in response to actual combat needs, and the research on the construction of corner reflector arrays has high practical value and application prospects. Summary of the invention

[0004] The object of the present invention is to provide a corner reflector array design method based on scattering center extraction, which utilizes a fast imaging simulation technology based on a bouncing ray method to analyze the scattering characteristics of different types of corner reflectors.

[0005] The technical solution to achieve the purpose of the present invention is as follows: In the first aspect, the present invention provides a method for designing a corner reflector array based on scattering center extraction, the steps of which are as follows:

[0006] Step 1: Based on the parameters of the radar echo and its incident wave, the attribute scattering center parameters of the target are extracted to perform the initial arrangement of the corner reflector array;

[0007] Step 2: Based on the initial arrangement of the corner reflector array, an iterative optimization corner reflector array model is constructed, with the structural similarity of the radar simulation image as the optimization target and the actual limitation of the corner reflector arrangement as a nonlinear constraint condition.

[0008] In a second aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first aspect when executing the program.

[0009] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0010] In a fourth aspect, the present invention provides a computer program product, comprising a computer program, which implements the steps of the method described in the first aspect when executed by a processor.

[0011] Compared with the prior art, the present invention has the following significant advantages: (1) the initial arrangement of the corner reflector array can be quickly generated by extracting the attribute scattering center, thereby improving the accuracy of the design arrangement of the corner reflector array; (2) the use of a non-uniform array arrangement can better fit the target scattering characteristics, thereby improving the target protection performance under high-resolution SAR. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a flow chart of a corner reflector array design method based on scattering center extraction. DETAILED DESCRIPTION

[0013] The present invention discloses a corner reflector array design method based on scattering center extraction. The method studies and analyzes the electromagnetic scattering characteristics of metal targets in complex scenes, and provides a feasible solution for the electromagnetic concealment of important targets. A corner reflector array with high radar image similarity to the target is generated, and the electromagnetic concealment performance of the corner reflector array arrangement is improved.

[0014] This method uses fast imaging simulation technology based on the bouncing ray method to analyze the scattering characteristics of different types of corner reflectors. On this basis, a method for constructing a corner reflector array based on the extraction of attribute scattering center parameters is proposed. The coordinate parameters extracted according to the attribute scattering center model are used for the initial arrangement of the corner reflector array, and the corner reflector array is optimized with structural similarity as the objective function, and finally a false target constructed by the corner reflector array is obtained. The simulation results show that the target concealment performance of the corner reflector array arrangement in complex scenes is above 90%, and it has a high similarity compared with the radar image of the target. Combined with Figure 1 The specific steps of this method are as follows:

[0015] Step 1: Initial arrangement of corner reflector array: Based on the parameters of radar echo and its incident wave, the attribute scattering center parameters of the target are extracted to perform preliminary design of the corner reflector array;

[0016] Step 2, corner reflector array optimization step: Based on the initial arrangement of the corner reflector array, an iterative optimization corner reflector array model is constructed, with the structural similarity of the radar simulation image as the optimization target, and the actual limitation of the corner reflector arrangement is a nonlinear constraint condition.

[0017] The corner reflector array is designed according to the attributed scattering center parameter model (ASC) described in step 1. The scattering center is a basic feature of high-resolution SAR images. The present invention extracts ASC parameters based on the radar echo of the SAR image. In the SBR method, each ray tube pair is at a distance r from the target, a pitch angle θ, and an azimuth angle Any observation point Two-dimensional fast imaging formula for:

[0018]

[0019] Among them, i is the frequency-dependent factor of the scattered electric field, R and C R Represent the coordinates in the range and azimuth directions respectively, Δk is the radar scanning beam interval, k0 is the radar, θ0 is the angle between the incident direction and the aperture surface, irays is the i-th ray tube, (ΔA) exit is the integration area of ​​the ray tube and the target surface, =(ΔA) exit The position vector at the center point A; is the observation point wave vector, For Perpendicular unit vector. sinc(u)=sin(u) / u,d i is the path length of the i-th ray from the incident point to the exit point. Represents the position coordinates of any vertex of the triangle face element, It represents the propagation distance of the ray before and after it touches the target.

[0020] Based on the above radar image signal, perform a two-dimensional inverse Fourier transform on it, and shift the transformed signal so that the small frequency is at the center. Then extract the scattering center from the target echo signal. The parameter information of ASC can characterize the dependence between the electromagnetic scattering characteristics and the signal frequency and angle. ASC is divided into distributed scattering centers and local scattering centers. The specific expression of ASC is as follows:

[0021]

[0022] Where Num represents the total number of scattering centers, E i A represents the scattered field of the i-th scattering center. i represents the scattering amplitude coefficient of the i-th scattering center, f represents the radar signal frequency, and f c represents the signal center frequency. i represents the length of the scattering center, represents the azimuth angle between the radar and the target, represents the tilt angle of the i-th scattering center, x i and i They represent the distance coordinates of the scattering center i relative to the reference point. i represents the frequency dependence factor. γ i represents the angular dependence factor of the scattering center. i >0, the scattering center i is a distributed scattering center; when L i = 0, the scattering center i is a local scattering center, and α∈{-1,0,1}. Since the ASC model has too many parameters, this paper adopts dictionary scaling and alternating optimization to reduce the computational complexity of the dictionary matrix. By combining the parameter grid dimension reduction method based on the full dictionary and the RELAX algorithm, the computational complexity is effectively reduced, and the performance of the algorithm at high resolution and the accuracy of the final parameter estimation are guaranteed. Finally, the number of scattering centers of the target and the parameters of each scattering center are obtained.

[0023] The iterative optimization method for the corner reflector array described in step 2: Use the bionic optimization algorithm to iteratively optimize the coordinates of the corner reflector array. Calculate the structural similarity between the corner reflector array and the radar image of the target as the fitness function, and compare the current mainstream bionic optimization algorithm, the gray wolf optimization algorithm

[21] The convergence effect and gradient descent of the iterative calculation process are better, so this section uses the Gray Wolf optimization algorithm to calculate the structural similarity between the corner reflector array and the radar image of the target as the fitness function, and the optimization parameters are The array has K corner reflectors, x k ,y k ,z k is the coordinate of the kth corner reflector on the Cartesian coordinate axis. φ k ,θ k are the angles between the kth corner reflector and the x, y, and z axes respectively. Before the optimization begins, the extracted scattering center parameters As the initial value, set the initial value of (z0,θ0,φ0) to 0 and substitute it into the corner reflector array optimization algorithm. In the gray wolf optimization algorithm, the first three wolves with the highest fitness scores are designated as α, β and δ, respectively. They lead other wolves ω to search towards the target position and update the position around α, β and δ. :

[0024]

[0025] in, and Respectively represent the distances between α, β, δ and other individuals; and Represent the current positions of α, β and δ respectively; is a random vector, is the position optimized at the current iteration step.

[0026] In general, the optimization problem can be described from three aspects: optimization variables, constraint functions, and objective functions. For the optimization problem of corner reflector arrays, the optimization goal is to maximize the structural similarity (SSIM) of the image. Structural similarity defines structural information from the perspective of image composition as a combination of three different factors: brightness, contrast, and structure. The expression of SSIM is:

[0027]

[0028] Let μ p and μ q are the average pixel intensity of images p and q, respectively, p and σ q are the standard deviations of images p and q, σ pq is the covariance of p and q. Ck1=(k1*Li) 2 , Ck2=(k2*Li) 2 , where Li represents the maximum value of the pixel value range of the image, which is generally 255. k1 and k2 take certain values ​​to avoid the denominator being 0. The SSIM value is between 0 and 1. The larger the SSIM, the higher the similarity of the two images. SSIM reaches the maximum index value of 1 if and only if the images and are the same.

[0029] Finally, considering the actual position requirements, the minimum distance between the two corner reflectors is defined as 0.5 meters. At the same time, to ensure that the coordinates of each corner reflector are within the position range required by the bouncing ray method, the entire optimization process of the array must comply with the following constraints:

[0030]

[0031] Among them, R min =(x min ,y min ,z min ),R max =(x max ,y max ,z max ) are the upper and lower limits of the iterative optimization coordinates.

[0032] The above are only preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the protection scope of the present invention. All components not specified in this embodiment can be implemented using existing technologies.

Claims

1. A corner reflector array design method based on scattering center extraction, characterized in that: Here are the steps: Step 1: Based on the parameters of the radar echo and its incident wave, the attribute scattering center parameters of the target are extracted to perform the initial arrangement of the corner reflector array; Step 2: Based on the initial arrangement of the corner reflector array, an iterative optimization corner reflector array model is constructed, with the structural similarity of the radar simulation image as the optimization target and the actual limitation of the corner reflector arrangement as a nonlinear constraint condition.

2. The method for designing a corner reflector array based on scattering center extraction according to claim 1, characterized in that: In step 1, a corner reflector array is designed according to a property scattering center parameter model; Scattering centers are the basic features of high-resolution SAR images. Based on the radar echoes of SAR images, ASC parameters are extracted. In order to obtain the echo information of the SAR image, the image is first subjected to a two-dimensional inverse Fourier transform, and the transformed signal is shifted so that the small frequency is at the center; then the scattering center is extracted from the target echo signal; the parameter information of ASC characterizes the dependence between the electromagnetic scattering characteristics and the signal frequency and angle; ASC is divided into distributed scattering center and local scattering center; the specific expression of ASC is as follows: Where Num represents the total number of scattering centers, E i represents the scattering field of the i-th scattering center; A i represents the scattering amplitude coefficient of the i-th scattering center, f represents the radar signal frequency, and f c represents the signal center frequency; L i represents the length of the scattering center, represents the azimuth angle between the radar and the target, represents the tilt angle of the i-th scattering center, x i and i They represent the distance coordinates of the scattering center i relative to the reference point; α i represents the frequency dependence factor; γ i represents the angular dependence factor of the scattering center; when L i >0, the scattering center i is a distributed scattering center; when L i When =0, the scattering center i is a local scattering center, and α∈{-1,0,1}.

3. The method for designing a corner reflector array based on scattering center extraction according to claim 2, characterized in that: In step 2, the coordinates of the corner reflector array are iteratively optimized using the Grey Wolf optimization algorithm; The structural similarity between the corner reflector array and the target’s radar image is calculated as the fitness function, and the optimization parameters are The array has K corner reflectors, x k ,y k ,z k is the coordinate of the kth corner reflector on the Cartesian coordinate axis; φ k ,θ k are the angles between the kth corner reflector and the x, y, and z axes respectively; before the optimization begins, the extracted scattering center parameters As the initial value, set the initial value of (z0,θ0,φ0) to 0 and substitute it into the corner reflector array optimization algorithm; in the gray wolf optimization algorithm, the first three wolves with the highest fitness scores are designated as α, β and δ, respectively, which lead other wolves ω to search towards the target position and update the position around α, β and δ. : in, and Respectively represent the distances between α, β, δ and other individuals; and Represent the current positions of α, β and δ respectively; is a random vector, is the position optimized by the current iteration step; The minimum distance between two corner reflectors is defined as 0.5 meters. To ensure that the coordinates of each corner reflector are within the position range required by the bouncing ray method, the entire optimization process of the array is subject to the following constraints: Among them, R min =(x min ,y min ,z min ),R max =(x max ,y max ,z max ) are the upper and lower limits of the iterative optimization coordinates.

4. A computer device comprising a memory, a processor and a computer program in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method according to any one of claims 1 to 3 are implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 3 are implemented.

6. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method described in any one of claims 1 to 3 are implemented.

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