Error-Constrained Entropy-Minimizing Strategies for Multi-UAV Deception Against Networked Radars.

IF 2.1 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Entropy Pub Date : 2025-06-18 DOI:10.3390/e27060653
Honghui Ban, Jifei Pan, Zheng Wang, Rui Cui, Yuting Ming, Qiuxi Jiang
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引用次数: 0

Abstract

In complex electromagnetic environments, spatial coupling uncertainties-position errors and timing jitter-increase false target information entropy, reducing strategy effectiveness and posing challenges for robust UAV swarm track deception. This paper proposes an error-constrained entropy-minimizing compensation framework to model radar/UAV errors and their spatial coupling. The framework establishes closed-form gate association conditions based on the principle of entropy minimization, ensuring mutual consistency of false target measurements across multiple radars. Two strategies are proposed to reduce false target information entropy: 1. Zonal track compensation forms dense "information entropy bands" around each preset false target by inserting auxiliary deception echoes, enhancing mutual information concentration in the measurement space; 2. Formation jamming compensation adaptively reshapes the UAV swarm into regular polygons, leveraging geometric symmetry to suppress spatial diffusion of position errors. Simulation results show that compared with traditional methods, the proposed approach reduces the spatial inconsistency entropy by 50%, improving false target consistency and radar deception reliability.

多无人机对网络雷达欺骗的误差约束熵最小化策略。
在复杂电磁环境下,空间耦合不确定性-位置误差和时序抖动-增加了假目标信息熵,降低了策略有效性,给鲁棒型无人机群航迹欺骗带来了挑战。本文提出了一种误差约束熵最小化补偿框架,用于模拟雷达/无人机误差及其空间耦合。该框架基于熵最小化原理建立闭式门关联条件,保证了多部雷达间假目标测量的相互一致性。提出了两种降低假目标信息熵的策略:区域航迹补偿通过插入辅助欺骗回波,在每个预设假目标周围形成密集的“信息熵带”,增强测量空间的互信息集中;2. 编队干扰补偿自适应地将无人机群重构为正多边形,利用几何对称性抑制位置误差的空间扩散。仿真结果表明,与传统方法相比,该方法将空间不一致熵降低了50%,提高了假目标一致性和雷达欺骗可靠性。
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
Entropy
Entropy PHYSICS, MULTIDISCIPLINARY-
CiteScore
4.90
自引率
11.10%
发文量
1580
审稿时长
21.05 days
期刊介绍: Entropy (ISSN 1099-4300), an international and interdisciplinary journal of entropy and information studies, publishes reviews, regular research papers and short notes. Our aim is to encourage scientists to publish as much as possible their theoretical and experimental details. There is no restriction on the length of the papers. If there are computation and the experiment, the details must be provided so that the results can be reproduced.
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