This letter focuses on adaptive target detection in the presence of multiple interference sources, which comprise clutter, thermal noise, noise-like jammers, and fully-correlated (or coherent) signals. In order to account for different operating scenarios, we formulate the problem at hand in terms of a multiple hypothesis test with several alternative hypotheses representative of each considered scenario. In this context, we devise a family of two-stage detection architectures capable of classifying the specific scenario and, hence, of working under different operating conditions. The performance analysis shows the effectiveness of the detector based upon the Generalized Information Criterion also in comparison with traditional adaptive decision schemes.

中文翻译：

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使用两个训练数据集在不利场景中创新的两级雷达检测架构


这封信重点关注存在多个干扰源的情况下的自适应目标检测，这些干扰源包括杂波、热噪声、类噪声干扰器和完全相关（或相干）信号。为了考虑不同的操作场景，我们根据多重假设检验来制定当前的问题，并使用代表每个考虑场景的几个替代假设。在这种情况下，我们设计了一系列两级检测架构，能够对特定场景进行分类，从而在不同的操作条件下工作。性能分析显示了基于广义信息准则的检测器与传统自适应决策方案的有效性。