Radar Target Detection Within Nonhomogeneous Sea Clutter via MSP-MIG Detectors

Subspace decomposition is a widely adopted approach for mitigating clutter interference in complex sea clutter scenarios. Based on the subspace decomposition principle, this paper expands the method to manifold space and presents a set of matrix information geometry (MIG) detectors with manifold subspace projection (MSP) for handling the target detection problem in nonhomogeneous sea clutter. According to the general method, the sample data are modeled as Hermitian positive-definite (HPD) matrices, and the clutter covariance matrix is estimated as the geometric mean of secondary HPD matrices. Through subspace projection, we map the HPD matrices onto a submanifold to enhance target–clutter separability. Three MSP-MIG detectors are put forward in line with different geometric measures. The experimental results show that our MSP-MIG detectors perform better than both traditional detectors and their non-MSP counterparts in nonhomogeneous sea clutter environment.