Performance results for a knowledge-aided clutter mitigation architecture

This paper describes performance results for a knowledge-aided (KA) space-time adaptive processing (STAP) architecture. The knowledge-aided parametric covariance estimation (KAPE) method forms the basis of the architecture. We employ high-fidelity simulated data from the DARPA KASSPER program in the analysis. For the scenarios considered, the KA-STAP architecture provides substantial performance improvement over traditional, post-Doppler STAP.