Structured Clutter Covariance Matrix Estimation for Airborne MIMO Radar With Limited Training Data

Abstract

This letter studies the estimation of structured clutter covariance matrix (CCM) for space-time adaptive processing (STAP)-based airborne multiin multiout (MIMO) radar with limited training data. The Kronecker-product-expansion structure of the CCM is considered, where each term involves two Kronecker product operators. By exploiting the low-rankness of two permutations of the CCM, we propose a novel estimator based on least squares penalized by two nuclear norms. The estimator is also extended by considering the linear structures of the CCM. We examine the structure of the proposed solution and demonstrate its superior performance through simulation studies.