Reduced-Rank STAP for Optimum Detection by Antenna-Pulse Selection

Space-time adaptive processing (STAP) is an effective strategy for clutter suppression in airborne radar systems. Limited training data, high computational load and the heterogeneity of training data constitute the main challenges in STAP. Most reduced-rank detection approaches, such as eigenvector decomposition, utilise a linear transformation to reduce the problem dimensionality. In this letter, we propose a new detection strategy based on selecting an optimum subset of antenna-pulse pairs associated with maximum separation between the target and the clutter trajectory. The proposed strategy reduces redundancy while addressing the above three interlinked challenges. An iterative Min-Max algorithm is proposed to solve the antenna-pulse selection problem, which is NP-hard combinatorial optimization. Extensive simulation results confirm the effectiveness of the proposed strategy.