The authors study the problem of compressive target detection in a single-frequency network (SFN)-based multistatic passive radar system (MS-PRS) consisting of multiple illuminators of opportunity (IOs) and one receiver. Firstly, a generalised likelihood ratio test (GLRT)-based SFN-based compressive subspace detector (SFN-CSD) is derived by exploiting the sparsity of the target echoes for the case of known noise variance. When the noise variance is unknown, an SFN-based unknown-noise (UN) compressive subspace detector is proposed, referred to as the SFN-UNCSD. Moreover, closed-form expressions of the probability of false alarm and detection of the proposed detectors are deriived. It is proved that the SNF-UNCSD has a constant false alarm rate (CFAR) property. Finally, numerical simulations are conducted to verify the theoretical analysis and illustrate the performance of the proposed detector relative to several benchmark detectors.

中文翻译：

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单频多基地无源雷达系统中基于 GLRT 的压缩子空间探测器

作者研究了基于单频网络 (SFN) 的多基地无源雷达系统 (MS-PRS) 中的压缩目标检测问题，该系统由多个机会照明器 (IO) 和一个接收器组成。首先，通过在已知噪声方差的情况下利用目标回波的稀疏性，导出基于广义似然比测试（GLRT）的基于 SFN 的压缩子空间检测器（SFN-CSD）。当噪声方差未知时，提出了一种基于SFN的未知噪声（UN）压缩子空间检测器，称为SFN-UNCSD。此外，还推导了所提出的检测器的误报和检测概率的封闭式表达式。证明SNF-UNCSD具有恒定虚警率(CFAR)特性。最后，进行数值模拟来验证理论分析并说明所提出的探测器相对于几个基准探测器的性能。