Geometric Measures for Information Geometry Detectors in Sea Clutter Environments

In this paper, the theory of matrix information geometry is studied with a particular focus on geometric structures over matrix manifolds. To address optimal geometric measure selection in Matrix Information Geometry (MIG) detectors, the performance of detectors based on typical geometric measures is compared in the context of weak target detection under sea clutter scenarios. Furthermore, the robustness of these geometric measures is systematically evaluated under non-ideal scenarios, including heterogeneous clutter distributions and discrete interference. Experimental results demonstrate that the KL divergence-based detector exhibits optimal detection performance. The results provide theoretical and empirical insights for optimal geometric measure selection in information geometry-based detectors for sea clutter environments.