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LPI Optimization Framework for Radar Network Based on Minimum Mean-Square Error Estimation

机译:基于最小均方误差估计的雷达网络LPI优化框架

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This paper presents a novel low probability of intercept (LPI) optimization framework in radar network by minimizing the Schleher intercept factor based on minimum mean-square error (MMSE) estimation. MMSE of the estimate of the target scatterer matrix is presented as a metric for the ability to estimate the target scattering characteristic. The LPI optimization problem, which is developed on the basis of a predetermined MMSE threshold, has two variables, including transmitted power and target assignment index. We separated power allocation from target assignment through two sub-problems. First, the optimum power allocation is obtained for each target assignment scheme. Second, target assignment schemes are selected based on the results of power allocation. The main problem of this paper can be considered in the point of views based on two cases, including single radar assigned to each target and two radars assigned to each target. According to simulation results, the proposed algorithm can effectively reduce the total Schleher intercept factor of a radar network, which can make a great contribution to improve the LPI performance of a radar network.
机译:通过基于最小均方误差(MMSE)估计最小化Schleher拦截因子,本文提出了一种新颖的雷达网络低拦截(LPI)优化框架。目标散射体矩阵的估计值的MMSE表示为估计目标散射特性的能力的度量。基于预定的MMSE阈值开发的LPI优化问题具有两个变量,包括发射功率和目标分配指数。我们通过两个子问题将功率分配与目标分配分开。首先,针对每个目标分配方案获得最佳功率分配。其次,基于功率分配的结果选择目标分配方案。可以从两种情况的角度来考虑本文的主要问题,包括分配给每个目标的单个雷达和分配给每个目标的两个雷达。仿真结果表明,该算法可以有效降低雷达网络的总Schleher截距因子,为提高雷达网络的LPI性能做出了巨大贡献。

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