3-dimensional STAP performance analysis using the cross-spectral metric

Abstract

Research done in recent years has clearly demonstrated large improvements in clutter suppression and target detection by including elevation adaptivity, otherwise described as 3-dimensional (3D) STAP. The paper further quantifies the performance gains garnered by 3D STAP by fixing the degrees of freedom (DOF) and varying the array dimensions to include the equivalently sized linear array. The focus is placed on performance bounds established by matched filter and 3D cross-spectral metric (CSM) SINR curves generated with known covariances. The mathematical extension of the CSM from 2D to 3D is shown to be straightforward, thus allowing the CSM to serve as a partially adaptive performance bound for eigenvalue-selection based 3D STAP algorithms.