摘 要：文章提出一种基于自适应滤波的多目标检测方法。将雷达回波等分成回波矩阵 Xi，计算 Xi 的协方差矩阵并进行特征值分解；利用特征值矩阵 D 计算奇异谱，估计主分量个数 Nev，以 Nev ＞ 3 作为门限判断回波矩阵 Xi 是否包含目标；通过特征矢量矩阵 V 构成的自适应滤波器对 Xi 滤波，估算滤波后回波脉冲的 Pareto 模型参数，生成 Pareto 随机序列；采用 K-L 散度识别目标回波，用峰值检测法确定各个目标位置。通过实测海杂波数据实验，验证了所提方法的有效性。
关键词：海杂波；多目标检测；特征值分解；自适应滤波；K-L 散度
DOI:10.19850/j.cnki.2096-4706.2022.04.019
中图分类号：TN957.51 文献标识码：A 文章编号：2096-4706（2022）04-0072-05
A Multi-target Detection Method Based on Adaptive Filtering in Sea Clutter Background
MA Hongguang, GUO Jinku, JIANG Qinbo, LIU Zhiqiang
(Xi’an Daheng Tiancheng IT Co. Ltd. Xi’an 710026, China)
Abstract: A multi-target detection method is proposed based on adaptive filtering. The radar echo is firstly evenly partitioned into echo matrices Xi . The covariance matrix of Xi is calculated and then the eigenvalue decomposition is performed. The singular spectrum is calculated via the eigenvalue matrix D, and the number of principal components Nev is determined. The threshold Nev>3 judges if targets are contained in Xi . The adaptive filtering is applied to Xi with the eigenvector matrix V. The model parameters of Pareto distribution are estimated for each filtered echo. The random series of Pareto distribution are generated. The target echoesare identified via K-L Divergence. The positions of targets are determined by peak finding technique. Trials have been conducted on the measured sea clutter datasets and the effectiveness of the proposed method is validated.
Keywords: sea clutter; multi-target detection; eigenvalue decomposition; adaptive filtering; K-L divergence
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作者简介：马红光（1959—），男，汉族，河南郑州人，教授（总师），博士，主要研究方向：非线性信息处理、目标探测与识别；郭金库（1980—），男，汉族，山东菏泽人，副教授（CEO），博士，主要研究方向：复杂电磁环境下目标检测与识别；姜勤波（1976—），男，汉族，江苏丹阳人，副教授，博士，主要研究方向：复杂系统建模与仿真、电子对抗；刘志强（1979—），男，汉族，四川崇州人，副教授，博士，主要研究方向：复杂系统建模与仿真、电子对抗。