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Fuzzy Chance-constrained Programming Based Security Information Optimization for Low Probability of Identification Enhancement in Radar Network Systems

机译:雷达网络系统中基于模糊机会约束规划的安全信息优化算法

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摘要

In this paper, the problem of low probability of identification (LPID) improvement for radar network systems is investigated. Firstly, the security information is derived to evaluate the LPID performance for radar network. Then, without any prior knowledge of hostile intercept receiver, a novel fuzzy chance-constrained programming (FCCP) based security information optimization scheme is presented to achieve enhanced LPID performance in radar network systems, which focuses on minimizing the achievable mutual information (MI) at interceptor, while the attainable MI outage probability at radar network is enforced to be greater than a specified confidence level. Regarding to the complexity and uncertainty of electromagnetic environment in the modern battlefield, the trapezoidal fuzzy number is used to describe the threshold of achievable MI at radar network based on the credibility theory. Finally, the FCCP model is transformed to a crisp equivalent form with the property of trapezoidal fuzzy number. Numerical simulation results demonstrating the performance of the proposed strategy are provided.
机译:本文研究了雷达网络系统的低识别率(LPID)改进问题。首先,导出安全信息以评估雷达网络的LPID性能。然后,在没有敌对拦截接收器的任何先验知识的情况下,提出了一种新颖的基于模糊机会约束规划(FCCP)的安全信息优化方案,以实现雷达网络系统中增强的LPID性能,其重点是在拦截器,而雷达网络上可达到的MI中断概率被强制大于指定的置信度。针对现代战场电磁环境的复杂性和不确定性,基于可信度理论,梯形模糊数用于描述雷达网络可达到的MI阈值。最后,将FCCP模型转换为具有梯形模糊数性质的清晰等效形式。数值仿真结果证明了所提策略的性能。

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  • 年度 2015
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  • 正文语种 {"code":"en","name":"English","id":9}
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