LDA-MIG Detectors for Maritime Targets in Nonhomogeneous Sea Clutter

TL;DR

This paper introduces LDA-MIG detectors that improve maritime target detection in complex sea clutter environments by leveraging geometric analysis of covariance matrices, especially effective with limited secondary data.

Contribution

It proposes a novel LDA-MIG detection framework using manifold optimization for better discrimination in nonhomogeneous sea clutter scenarios.

Findings

LDA-MIG detectors outperform existing methods in simulated and real radar data.

The approach effectively handles limited secondary data in complex clutter environments.

Proposed detectors show robustness against interference and heterogeneity.

Abstract

This paper deals with the problem of detecting maritime targets embedded in nonhomogeneous sea clutter, where limited number of secondary data is available due to the heterogeneity of sea clutter. A class of linear discriminant analysis (LDA)-based matrix information geometry (MIG) detectors is proposed in the supervised scenario. As customary, Hermitian positive-definite (HPD) matrices are used to model the observational sample data, and the clutter covariance matrix of received dataset is estimated as geometric mean of the secondary HPD matrices. Given a set of training HPD matrices with class labels, that are elements of a higher-dimensional HPD matrix manifold, the LDA manifold projection learns a mapping from the higher-dimensional HPD matrix manifold to a lower-dimensional one subject to maximum discrimination. In the current study, the LDA manifold projection, with the cost function maximizing between-class distance while minimizing within-class distance, is formulated as an optimization problem in the Stiefel manifold. Four robust LDA-MIG detectors corresponding to different geometric measures are proposed. Numerical results based on both simulated radar clutter with interferences and real IPIX radar data show the advantage of the proposed LDA-MIG detectors against their counterparts without using LDA as well as the state-of-art maritime target detection methods in nonhomogeneous sea clutter.