Distributed Target Detection Based on the Volume Cross-Correlation Function

Abstract

This letter addresses the detection of a subspace distributed target signal obscured by disturbance. The disturbance consists of a clutter component with an unknown subspace structure and a white noise component with unknown noise power. A detection strategy is proposed based on the volume cross-correlation function, which provides a metric that measures the linear (in) dependency between two subspaces. Simulation results indicate that the proposed detector can achieve better performance than several peer methods, without resorting to secondary data and a priori knowledge about the clutter subspace including its rank.