Multi-array systems are widely used in sonar and radar applications. They can improve communication speeds, target discrimination, and imaging. In the case of a multibeam sonar system that can operate two receiving arrays, we derive new adaptive to improve detection capabilities compared to traditional sonar detection approaches. To do so, we more specifically consider correlated arrays, whose covariance matrices are estimated up to scale factors, and an impulsive clutter. In a partially homogeneous environment, the 2-step Generalized Likelihood ratio Test (GLRT) and Rao approach lead to a generalization of the Adaptive Normalized Matched Filter (ANMF) test and an equivalent numerically simpler detector with a well-established texture Constant False Alarm Rate (CFAR) behavior. Performances are discussed and illustrated with theoretical examples, numerous simulations, and insights into experimental data. Results show that these detectors outperform their competitors and have stronger robustness to environmental unknowns.

翻译：多阵列系统广泛应用于声呐和雷达领域，可提升通信速率、目标识别与成像能力。针对可同时运行两个接收阵列的多波束声呐系统，本文推导了新型自适应检测方法，相较于传统声呐检测手段显著提升了探测性能。为此，我们重点研究了协方差矩阵仅需估计至尺度因子的相关阵列，以及脉冲杂波环境。在部分均匀环境中，两步广义似然比检验（GLRT）与Rao方法导出了自适应归一化匹配滤波器（ANMF）检验的推广形式，并构建了具备纹理恒虚警率（CFAR）特性的等效简化数值检测器。通过理论示例、大量仿真及实验数据验证，结果表明所提检测器性能优于现有方法，且对环境未知因素具有更强的鲁棒性。