A combined STAP/DPCA algorithm for enhanced endoclutter target detection

Abstract

Displaced Phase Center Antenna (DPCA) and Space-Time Adaptive Processing (STAP) are two general methods to cancel clutter in order to detect small, slowly moving targets that may be obscured by clutter. To detect these targets, the radar detection threshold needs to be as low as possible to ensure some minimum probability of detection (Pd). Unfortunately, lowering the radar threshold naturally results in a higher false alarm rate. Although there are standard methods such as M of N to reduce the false alarms, new techniques can potentially drive the false alarm rate down even further. Many “theoretical” papers have shown that STAP can be designed to outperform DPCA because of its potential additional “degrees-of-freedom”. However, in “practice,” this isn’t always the case. For example, it is well known that STAP can have training issues in heterogeneous clutter. Typically, a radar signal processor will implement one method or the other to detect these small endoclutter targets. The technique being explored here is a two-fold approach in which the existing STAP code first processes the data in order to find a list of candidate targets. Next, a DPCA technique is also used to find a separate list of candidate detections from the same data. Although the algorithms are working on the same data, the processing is “independent” between them so the target lists are different. After both techniques have finished processing, the modified radar signal processing code “intelligently” combines the two detection lists into a single detection list. It will be shown that the combined list of detections from the two methods results in better detection performance than either method used separately.