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Bi-Phase Compound-Gaussian Mixture Model of Sea Clutter and Scene-Segmentation-Based Target Detection

机译：海洋杂波的双相复合高斯混合模型和基于场景分割的目标检测

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摘要

In high-resolution maritime surveillance radars, sea clutter exhibits highly spatial heterogeneity due to modulation of long waves with wavelengths longer than the width of one range cell. Compound-Gaussian model (CGM) fails to characterize the heterogeneous high-resolution sea clutter in both amplitude distribution and Doppler spectrum. In this article, a bi-phase compound-Gaussian mixture model (BP-CGMM) is proposed to characterize the heterogeneous sea clutter. In the BP-CGMM, spatial resolution cells are grouped into two disjoint sets, and the sea clutter in each set is represented by one CGM with inverse Gamma-distributed texture. The spectral heterogeneity indicates that sea clutter vectors at spatially adjacent resolution cells in one set share the same speckle covariance matrix, while that at two adjacent spatial cells separated in the two sets often have different speckle covariance matrices. The BP-CGMM is validated by a mass of measured high-resolution sea clutter data. Moreover, under the BP-CGMM, a detection method based on batch test is given to detect sea-surface small targets, which is composed of scene segmentation, by the aid of Bayesian threshold and morphological filtering, and adaptive generalized likelihood ratio test linear-threshold detector (GLRT-LTD) separately in each set. The detection method is verified by measured data with small targets under test. The experimental results show that it attains better detection performance than the adaptive GLRT-LTD under the CGM of sea clutter.
机译：在高分辨率海上监控雷达中，海杂波由于具有比一个范围细胞的宽度长的波长的长波的调节而表现出高度空间的异质性。复合高斯模型（CGM）未能在幅度分布和多普勒光谱中表征异质高分辨率海杂波。在本文中，提出了一种双相复合高斯混合模型（BP-CGMM）以表征异质海洋杂波。在BP-CGMM中，空间分辨率小区被分组成两个不相交的组，并且每个组中的海杂波由一个CGM表示，其具有逆伽马分布式纹理。光谱异质性指示在一个集合中的空间相邻分辨率单元处的海杂波矢量共享相同的散斑协方差矩阵，而在两组中分离的两个相邻的空间单元通常具有不同的散斑协方差矩阵。 BP-CGMM由大量测量的高分辨率海杂波数据验证。此外，在BP-CGMM下，基于批量测试的检测方法检测海面小目标，其由贝叶斯阈值和形态过滤的借助于场景分割，以及自适应广义似然比测试线性 - 每个套件中的阈值探测器（GLRT-LTD）。通过测量数据验证检测方法，具有下定目标的小目标。实验结果表明，它比海洋杂波CGM下的Adaptive Glrt-Ltd达到更好的检测性能。

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