基于信噪比分集的分布式MIMO雷达目标检测

Qinzhen Hu, Hongtao Su, Shenghua Zhou, Ziwei Liu
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引用次数: 4

摘要

本文研究了分布式多输入多输出雷达的信噪比分集目标检测问题。信噪比分集是指空间分集信道中的信噪比不同,这可能会降低检测性能。此外,信噪比的先验知识通常是不可用的。考虑到这两个方面,我们提出了累积贡献率广义似然比检验(CCR-GLRT)检测器。在每个空间分集信道中,利用GLRT规则获取局部检验统计量。在融合中心,使局部测试统计量的CCR刚好大于给定的阈值因子。对满足给定因子的局部检验统计量进行汇总,得到全局检验统计量。仿真结果表明,CCR-GLRT检测算法在信噪比多样性方面优于传统的集中式GLRT检测算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Target detection with SNR diversity for distributed MIMO radar
In this paper, we consider a target detection problem with the signal-to-noise ratio (SNR) diversity for a distributed multiple-input multiple-output radar. The SNR diversity means that the SNRs in spatial diversity channels are different, which may degrade the detection performance. Further, the prior knowledge of the SNR is usually unavailable. Considering both aspects, we propose a cumulative contribution rate generalized likelihood ratio test (CCR-GLRT) detector. In each spatial diversity channel, the GLRT rule is exploited in order to obtain the local test statistic. In the fusion center, make the CCR of the local test statistics just greater than a given threshold factor. The global test statistic can be obtained by summarizing these local test statistics which satisfy the given factor. Simulation results show that our proposed CCR-GLRT detection algorithm outperforms the conventional centralized GLRT detection algorithm with the SNR diversity.
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