Relative Entropy Based Jamming Signal Design Against Radar Target Detection

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Zhou Xu;Bo Tang;Weihua Ai;Jiahua Zhu
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引用次数: 0

Abstract

In modern electronic warfare, active jamming is an important way to prevent the target from being detected by the radar sensors. This paper considers the problem of designing effective jamming signals with limited jamming power. By taking the relative entropy as the figure of merit, we formulate the jamming signal design as a matrix optimization problem which is Non-Polynomial (NP) hard in general. To solve the resultant problem, we conceive an iterative algorithm, named by Relative Entropy Jamming Optimization Algorithm (REJOA), based on combining the Majorization Minimization (MM) technique and the matrix factorization together. The conceived algorithm updates the optimization variable in a closed form (or semi-closed form) at each iteration, and guarantees theoretical convergence. Finally, we compare our design with the Mutual Information (MI) based design and the Signal to Jamming plus Noise Ratio (SJNR) based design through numerical experiments. Results highlight that, compared with the state-of-the-art designs, our design achieves better jamming performance with the same jamming power.
基于相对熵的雷达目标探测干扰信号设计
在现代电子战中,主动干扰是防止目标被雷达探测到的重要手段。本文考虑了在有限干扰功率下设计有效干扰信号的问题。以相对熵为优值,将干扰信号的设计化为一般非多项式(NP)难的矩阵优化问题。为了解决由此产生的问题,我们提出了一种基于最大化最小化技术和矩阵分解相结合的迭代算法,称为相对熵干扰优化算法(rejoy)。该算法在每次迭代时以封闭形式(或半封闭形式)更新优化变量,保证了理论收敛性。最后,通过数值实验将该设计与基于互信息(MI)的设计和基于信噪比(SJNR)的设计进行了比较。结果表明,与现有设计相比,在相同的干扰功率下,我们的设计获得了更好的干扰性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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