Space-time adaptive processing for phased-multiple-input–multiple-output radar in the non-homogeneous clutter environment

This study presents some new methods for space-time adaptive processing for airborne multiple-input-multiple-output (MIMO) radar with co-located antennas in the non-homogeneous environment. The presented signal model is a general model for airborne phased-MIMO radar which can easily switch between conventional phased-array radar and MIMO radar to enjoy the advantages of the MIMO radar without sacrificing the main advantage of the phased-array radar which is the coherent processing gain at the transmitting side. In the non-homogeneous environment, the training data with the same statistical interference characteristics is not available to estimate interference covariance matrix, the authors present two space-time adaptive processing (STAP) approaches. The first one is based on the orthogonal projection on the clutter subspace which is applicable for known clutter signature scenarios. The matrix which describes the signature of ground clutter for airborne phased-MIMO radar is derived. For unknown clutter subspace, they propose the deterministic phased-MIMO STAP (also known as direct data domain approach) which suppresses the interference signal without the requirement for an interference covariance matrix. The parameters of deterministic phased-MIMO STAP are determined to maximise the degree of freedoms. Simulations are provided to demonstrate the performance of the proposed STAP approaches in the non-homogeneous environments.