Adaptive radar detection in diffuse multipath environments

Abstract

We deal with the problem of detecting point-like targets in diffuse multipath environments. We model the target echo as the superposition of a deterministic signal with an unknown scaling factor (due to the direct path) plus a zero-mean Gaussian random vector with an unknown covariance matrix (accounting for echoes from the glistening surface). Hence, we devise a constrained Generalized Likelihood Ratio Test (GLRT) for the resulting hypothesis testing problem, enforcing the primary data covariance matrix (due to both interference and multipath echoes) to belong to a neighborhood of the secondary data sample covariance matrix. Remarkably, the proposed decision scheme ensures the desirable Constant False Alarm Rate (CFAR) property with respect to the unknown parameters of the interference. The performance assessment is conducted on simulated data in terms of detection probability (P d ) also in comparison with existing solutions in open literature. The results highlight the effectiveness of the new approach to cope with diffuse multipath environments.