This paper addresses adaptive detection of a range distributed target in the presence of dominant heterogeneous clutter, which is (possibly) low-rank and lies in a known subspace, plus Gaussian thermal noise. First, this problem is transformed into an equivalent binary hypothesis test with observations having block-diagonal covariance matrices. Then an invariance analysis is conducted on the resulting hypothesis test. Data and unknown parameters are compressed into a maximal invariant and an induced maximal invariant, respectively, w.r.t. a suitable transformation group. This suggests to focus attention on invariant detectors and to establish the relationship between invariance and constant false alarm rate (CFAR) property. According to this guideline, two tunable invariant detectors exploiting the aforementioned covariance structure are devised, and they are shown to ensure bounded CFAR and standard CFAR properties, respectively. Finally, the CFAR behavior of the proposed detectors as well as their detection performance is assessed via numerical simulations.

中文翻译：

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基于不变性理论的低秩异构杂波自适应雷达检测

本文讨论了在存在显着异质杂波的情况下对距离分布目标的自适应检测，该杂波（可能）是低秩的，位于已知子空间中，外加高斯热噪声。首先，利用具有块对角协方差矩阵的观测值，将此问题转换为等效的二元假设检验。然后对所得的假设检验进行不变性分析。数据和未知参数分别通过适当的转换组压缩为最大不变量和诱导最大不变量。这建议将注意力集中在不变检测器上，并建立不变与恒定误报率（CFAR）属性之间的关系。根据该指南，设计了两个利用上述协方差结构的可调不变检测器，并显示它们分别确保有界CFAR和标准CFAR属性。最后，通过数值模拟评估了所提出的探测器的CFAR行为及其探测性能。