Recently, the matrix information geometry (MIG) detector, which characterizes sample data as a Hermitian positive definite (HPD) matrix located on the HPD manifold, was rapidly developed and demonstrated extraordinary performance in numerous applications, especially in heterogeneous clutter backgrounds. In this article, the geodesic normal coordinate (GNC)-based manifold filter is proposed to improve the detection performance of the MIG detector in strong clutter backgrounds. Using the GNC system, the distribution of target echoes and clutter on the high-dimensional manifold can be visualized and analyzed. Moreover, by exploiting the information concerning the distribution of matrices, the manifold filter is proposed to enhance target echoes and suppress strong clutter. Then, the manifold-filter-based MIG detector is designed, and its superiority is theoretically analyzed. The actual clutter data are utilized to verify the effectiveness of the proposed method. The results show that the proposed manifold filter achieves a signal-to-clutter ratio improvement of more than 5 dB over the existing MIG detectors.

中文翻译：

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用于目标检测的基于测地法线坐标的流形滤波

最近，将样本数据表征为位于 HPD 流形上的 Hermitian 正定 (HPD) 矩阵的矩阵信息几何 (MIG) 检测器得到了迅速发展，并在众多应用中表现出非凡的性能，尤其是在异质杂波背景中。在本文中，提出了基于测地法线坐标（GNC）的流形滤波器，以提高 MIG 探测器在强杂波背景下的检测性能。使用 GNC 系统，可以可视化和分析目标回波和杂波在高维流形上的分布。此外，通过利用有关矩阵分布的信息，提出了流形滤波器来增强目标回波并抑制强杂波。然后，设计了基于流形滤波器的 MIG 检测器，并对其优越性进行了理论分析。实际杂波数据用于验证所提方法的有效性。结果表明，与现有的 MIG 检测器相比，所提出的流形滤波器实现了超过 5 dB 的信杂比改进。