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Cooperative game-theoretic power allocation algorithm for target detection in radar network

机译:雷达网络目标检测的合作博弈理论功率分配算法

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This paper investigates the problem of power allocation for radar network in a cooperative game-theoretic framework such that the low probability of intercept (LPI) performance can be improved. Taking into consideration both the transmit power constraint and the minimum signal-to-interference-plus-noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game (NBPAG) based on LPI is formulated, whose objective is to improve the LPI performance by optimizing the transmit power allocation in radar network for a predefined S-INR threshold. First, a novel SINR-based network utility function is defined as a metric to evaluate power allocation. Then, the existence and uniqueness of the Nash bargaining solution (NBS) are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Theoretic analysis and simulations are provided to evaluate the effectiveness of the proposed algorithm.
机译:本文研究了在合作博弈理论框架下雷达网络的功率分配问题,从而可以提高低拦截概率(LPI)性能。考虑到每个雷达的发射功率约束和最小信干噪比(SINR)要求,制定了基于LPI的合作纳什议价功率分配博弈(NBPAG),其目的是提高通过针对预定义的S-INR阈值优化雷达网络中的发射功率分配来提高LPI性能。首先,将基于SINR的新型网络效用函数定义为评估功率分配的指标。然后,分析证明了纳什议价解决方案(NBS)的存在性和唯一性。最后,开发了迭代的纳什讨价还价算法,该算法可快速收敛到合作博弈的帕累托最优均衡。提供理论分析和仿真以评估所提出算法的有效性。

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