基于极化与距离像特征融合的雷达导引头角反射器鉴别方法

doi:10.12305/j.issn.1001-506X.2024.11.08

摘要/Abstract

摘要：

角反射器形成的强假目标干扰给反舰导弹雷达导引头目标识别带来了严峻的挑战。为提高反舰导弹雷达导引头抗冲淡式角反射器干扰能力, 提出一种基于极化与高分辨距离像(high resolution range profile, HRRP)多特征融合的角反射器鉴别方法。结合3种场景下的实验数据, 首先从海杂波中提取雷达导引头目标回波信号; 其次, 分析了角反和舰船回波的峰值个数、径向尺寸等5个距离像特征, 以及极化相关系数均值等3个极化特征。实验数据处理结果表明, 舰船与单个角反特征差异明显, 与阵列角反特征差异减小; 然后利用支持向量机(support vector machine, SVM)方法, 基于实验数据设计5组测试, 分别检验了单特征和多特征融合的鉴别性能。测试结果表明, 单特征鉴别方法性能不稳定, 而所提出的三特征融合鉴别方法更具稳健性, 在5组测试中鉴别准确率均达到92.86%以上。

关键词: 雷达导引头, 角反射器, 目标鉴别, 抗干扰

Abstract:

The strong false target interference formed by the corner reflector poses a serious challenge to the target identification of the anti-ship missile radar seeker. In order to improve the radar seeker's ability of anti diluted corner reflector jamming, an identification method of corner reflector based on multi-feature fusion of polarization and high resolution range profile (HRRP) is proposed. Firstly, combining the experimental data in three scenarios, the target echo signals of radar seeker are extracted from the sea clutter. Secondly, five range profile features, such as peak number and radial dimension, and three polarization features, such as mean of polarization coherence, are analyzed from the corner reflector and ship echoes. The processing results of the experimental data show that the feature difference is obvious between the ship and the single corner reflector, while the difference decreases between the ship and the array. Then, using the support vector machine (SVM) method, five tests are designed based on the experimental data, and the discrimination performance of single-feature and multi-feature fusion is examined respectively. The test results show that the single-feature identification method is not stable, while the proposed three-feature fusion identification method is more robust, and the identification accuracy reaches more than 92.86% in five tests.

Key words: radar seeker, corner reflector, target identification, anti-jamming

中图分类号:

TN974

韩静雯, 杨勇, 连静, 吴国庆, 王雪松. 基于极化与距离像特征融合的雷达导引头角反射器鉴别方法[J]. 系统工程与电子技术, 2024, 46(11): 3658-3670.

Jingwen HAN, Yong YANG, Jing LIAN, Guoqing WU, Xuesong WANG. Identification method of corner reflector based on polarization and HRRP feature fusion for radar seeker[J]. Systems Engineering and Electronics, 2024, 46(11): 3658-3670.

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场景	目标	干扰	信杂比/dB	干信比/dB	数据量/帧
1	2艘中型舰船	2个角反	14.5	17.6	10
2	大型舰船	二角反阵列	26.8	-2.9	19
3	小型舰船	角反	4.2	25.2	10

测试	训练集来源	测试集来源	训练集数据	测试集数据	先验信息
1	A类舰船单个角反	同训练集	随机取场景1 75%样本数据	场景1剩余25%样本数据	已知
2	B类舰船阵列角反	同训练集	随机取场景2 75%样本数据	场景2剩余25%样本数据	已知
3	A、B类舰船单个角反、阵列角反	同训练集	场景1所有数据+场景2任取10帧数据	场景2剩余9帧样本数据	已知
4	A、B类舰船单个角反、阵列角反	C类舰船单个角反	场景1所有数据+场景2任取10帧数据	场景3所有数据	未知
5	A类舰船单个角反	B类舰船阵列角反	场景1所有数据	随机取训练集1/3数量的场景2数据	未知

特征参数	测试1	测试2	测试3	测试4	测试5
NP	0.998 7	1.000 0	0.750 7	0.500 0	0.507 8
径向尺寸	1.000 0	1.000 0	0.750 0	0.864 1	0.507 8
总半峰宽	0.997 4	1.000 0	0.967 0	0.783 4	0.507 8
目标幅度方差	0.994 8	0.917 3	0.750 7	0.772 7	0.508 6
平均差分幅度	0.996 1	0.740 9	0.876 4	0.500 0	0.753 7
极化相关系数均值	0.960 9	0.736 8	0.752 1	0.919 5	0.540 3
极化相关系数平滑度	0.898 4	0.848 9	0.766 5	0.785 2	0.624 6
最强点平均位置差	0.998 7	0.992 4	0.956 7	0.989 9	0.808 4

参数	测试1	测试2	测试3	测试4	测试5
三特征联合	1	1	0.995 2	0.992 9	0.928 6

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