基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法

于乐新; 张慧; 龚琳舒; 姜弢

doi:10.19693/j.issn.1673-3185.02296

基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法

doi: 10.19693/j.issn.1673-3185.02296

于乐新^1,,
张慧¹,
龚琳舒²,
姜弢^1, ,

1.
哈尔滨工程大学信息与通信工程学院，黑龙江哈尔滨 150001
2.
上海机电工程研究所，上海 201109

基金项目: 国家自然科学基金资助项目（51809056）

详细信息

作者简介:
于乐新，男，1994年生，硕士生。研究方向：雷达抗干扰。E-mail：15922075253@163.com

姜弢，男，1973 年生，博士，教授。研究方向：电波传播及电磁环境建模与仿真。E-mail：jiangtao@hrbeu.edu.cn

通信作者:
姜弢

中图分类号: U665.22
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出版历程
- 收稿日期: 2021-02-22
- 修回日期: 2021-06-07
- 网络出版日期: 2022-04-01
- 刊出日期: 2022-04-20

Countermeasures for range false target jamming based on quasi Karhunen-Loève translate basis dictionary learning method

YU Lexin^1
,,
ZHANG Hui¹,
GONG Linshu²,
JIANG Tao^{1
, ,}

1.
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
2.
Shanghai Electro-Mechanical Engineering Institute, Shanghai 201109, China

基于准Karhunen-Loève变换基的字典学习抗距离假目标干扰方法由于乐新，等创作，采用知识共享署名4.0国际许可协议进行许可。

摘要

摘要: 目的波形分集技术是一种有效对抗距离假目标干扰的舰载雷达抗干扰的措施，但在强干扰环境下信号失配产生的较高旁瓣依然会影响雷达探测性能。因此，为了能够更好地抑制大功率距离假目标的干扰，提出一种基于字典学习的干扰消除方法。方法首先，建立与目标和干扰信号对应的初始化字典；然后，将选取的原子与初始化字典生成自相关矩阵模板，采用非齐次线性均方估计求得匹配系数，再通过模板与匹配系数分别构建目标和干扰对应的近似准Karhunen-Loèv变换基；最后，利用凸优化算法实现目标和干扰信号的分离与恢复。结果仿真试验结果表明，所提方法可以在干信比30 dB时有效对抗一个或多个距离假目标的干扰。结论相较于传统雷达波形分集技术，该方法在高干信比环境下依然保持良好的抗干扰性能，可用于舰载雷达对抗大功率距离假目标干扰。
- 抗距离假目标干扰 /
- 波形分集 /
- 字典学习 /
- 准Karhunen-Loève变换
Abstract: Objectives Waveform diversity technology is an effective anti-jamming measure against range false target jamming. However, in an environment of strong energy jamming, the high side-lobe caused by the jamming signal mismatch will still affect the detection performance of the radar. To this end, a dictionary learning method is proposed in order to better suppress and eliminate high-power jamming. Methods First, an initialization dictionary corresponding to the target and jamming signals is established. Second, the initialization dictionary and selected atoms are used to generate an autocorrelation matrix template, and the matching coefficient is obtained using the non-homogeneous linear mean square estimation. Next, an approximate quasi-Karhunen-Loève transform（Q-KLT） basis corresponding to the target and jamming signals is constructed by template and matching coefficients respectively. Finally, a convex optimization algorithm is used to separate and recover the target and jamming signals. Results The simulation results show that the proposed method can effectively counter the jamming of one or multiple range false targets at a 30 dB jamming-to-signal ratio. Conclusions Compared with the traditional waveform diversity technology, the proposed method still maintains good anti-jamming performance in high jamming-to-signal ratio environments, and can be used by shipboard radar to counter range false target jamming.
- anti-jamming of range false target /
- waveform diversity /
- dictionary learning /
- quasi Karhunen-Loève transform

HTML全文

图 1 尖峰检测法估计干扰滞后周期个数的工作流程图

Figure 1. Flow chart of estimating the number of jamming lag periods using spike detection method

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图 2 干扰抑制仿真结果

Figure 2. Simulation results of jamming suppression

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图 3 Gini系数随着JSR变化曲线

Figure 3. The Gini coefficient varying with JSR

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图 4 干扰抑制后的PSLR值随着JSR变化曲线

Figure 4. The PSLR value after jamming suppression varying with JSR

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