This paper addresses the problem of target detection against a background of Gaussian clutter by using frequency snapshots with reduced degrees of freedom (DOF). We derive the optimal detector and detection performance under the Neyman-Pearson criterion for general frequency snapshot selection with arbitrary DOF. When the clutter statistics are unknown, we use a uniformly random frequency snapshot selection method and show how the DOF employed affects the detection performance. When the clutter return follows a stationary Gaussian distribution with slowly varying power spectral density, the optimal selection is derived. When the clutter is composed of reflected versions of the transmitted waveforms, a greedy-based method for selecting the frequency snapshots is presented. Numerical experiments show that a receiver with reduced DOF can lead to detection performance which is very close to that of the receiver with full DOF.

中文翻译：

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用于高斯杂波下目标检测的频域减小自由度的接收机设计


本文通过使用降低自由度 (DOF) 的频率快照来解决高斯杂波背景下的目标检测问题。我们在 Neyman-Pearson 准则下推导了任意 DOF 的通用频率快照选择的最佳检测器和检测性能。当杂波统计未知时，我们使用均匀随机频率快照选择方法，并显示所采用的自由度如何影响检测性能。当杂波返回遵循功率谱密度缓慢变化的平稳高斯分布时，就会得出最佳选择。当杂波由发射波形的反射版本组成时，提出了一种基于贪婪的方法来选择频率快照。数值实验表明，具有减小自由度的接收器可以导致非常接近于具有全自由度的接收器的检测性能。