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罗晓萍, 廖可非, 欧阳缮, 杜毅. 基于聚类相参叠加的频率分集阵列雷达目标成像方法[J]. 桂林电子科技大学学报, 2023, 43(2): 99-105.
引用本文: 罗晓萍, 廖可非, 欧阳缮, 杜毅. 基于聚类相参叠加的频率分集阵列雷达目标成像方法[J]. 桂林电子科技大学学报, 2023, 43(2): 99-105.
LUO Xiaoping, LIAO Kefei, OUYANG Shan, DU Yi. Based on the clustering of the coherent superposition frequency diversity array radar target imaging method[J]. Journal of Guilin University of Electronic Technology, 2023, 43(2): 99-105.
Citation: LUO Xiaoping, LIAO Kefei, OUYANG Shan, DU Yi. Based on the clustering of the coherent superposition frequency diversity array radar target imaging method[J]. Journal of Guilin University of Electronic Technology, 2023, 43(2): 99-105.

基于聚类相参叠加的频率分集阵列雷达目标成像方法

Based on the clustering of the coherent superposition frequency diversity array radar target imaging method

  • 摘要: 针对后向投影算法(BP算法)对多目标进行成像时存在目标位置模糊以及旁瓣高的问题,在分析FDA目标回波幅值所具有的累加特性后,提出了一种基于聚类相参叠加的频率分集阵列雷达目标成像方法。在分析及仿真BP算法成像过程中,发现目标点具有能量集中特性且与虚像点能量存在差异性,而K均值聚类算法能充分利用目标点的这些特性,对雷达成像区域目标点进行特征提取及分类,并只对分类后特定簇的网格点进行时延补偿,之后将回波幅值进行叠加,从而得到成像区域中时延补偿网格点的能量值,最终实现多目标清晰二维成像。仿真实验结果表明,该方法可有效解决BP算法对多目标进行成像时目标位置模糊及旁瓣高的问题,同时提高了成像结果的精确度。

     

    Abstract: Aiming at the problem of blurred target position and high sidelobe when the back projection algorithm (BP algorithm) is imaging multi-targets, after analyzing the accumulation characteristics of the FDA target echo amplitude, a target imaging method of frequency diversity array radar based on clustering and coherent superposition is proposed. In the analysis and Simulation of BP algorithm imaging process, it is found that the target point has the characteristics of energy concentration and energy difference with the virtual image point. The K-means clustering algorithm can make full use of these characteristics of the target point to extract and classify the target points in the radar imaging area, and only compensate the time delay of the grid points of the specific cluster after classification, and then stack the echo amplitude, Thus, the energy value of the time delay compensation grid points in the imaging region is obtained, and finally the multi-target clear two-dimensional imaging is realized. The simulation results show that the proposed method can effectively solve the problems of fuzzy position and high sidelobe when BP algorithm imaging multi-target, and improve the accuracy of imaging results.

     

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