Enhancing Space-Time Adaptive Processing Through the Slepian Transform1

A High Dynamic Range Space-Time Adaptive Processing (HDR-STAP) improves cancellation of large interference sources by using a Fast Slepian Transform to capture and cancel more clutter energy than other STAP approaches. STAP’s efficacy relies on its ability to estimate clutter interference across space (antenna elements) and time (pulses) but hits limitations due to interference strength and spectrum spread. In addition to clutter cancellation limits, the target signal can suffer a STAP processing loss. This paper focuses on the signal to clutter enhancement metric to compare performance of different STAP techniques. HDR-STAP projects the estimated clutter covariance matrix onto the Slepian basis functions. A limited number of orthogonal Slepian basis functions are defined using the signals’ sample rate and a selected finite bandwidth. HDR-STAP takes advantage of a Fast Slepian transform (FST) from Karnik, et. all [1], producing a practical implementation. This article demonstrates that HDR-STAP removes more clutter than sample matrix inversion (SMI) and Eigendecomposition STAP while achieving signal losses below those predicted by the Reed, Mallet, and Brennon (RMB) rule.