Session 6A.4
Improving knowledge-aided STAP performance using past CPI data

Douglas A. Page - ALPHATECH, Inc., Steven Scarborough - ALPHATECH, Inc., Gregory Owirka - ALPHATECH, Inc., Steven Crooks - ALPHATECH, Inc.

Wed, 28 April 2004, 10:20 AM - 12:00 PM

Abstract

A technique for incorporating past coherent processing interval (CPI) radar data into knowledge-aided space-time adaptive processing (KASTAP) is described. The technique forms earth-based clutter reflectivity maps to provide improved knowledge of clutter statistics in nonhomogeneous terrain environments. The maps are utilized to calculate predicted clutter covariance matrices as a function of range. Using a data set provided under the DARPA Knowledge-Aided Sensor Signal Processing and Expert Reasoning (KASSPER) program, predicted clutter statistics are compared to measured statistics to verify the accuracy of the approach. Robust STAP weight vectors are calculated using a technique that combines covariance tapering, adaptive estimation of gain and phase corrections, knowledge-aided pre-whitening, and eigenvalue rescaling. Several performance metrics are calculated, including signal-to-interference plus noise (SINR) loss, target detections and false alarms, receiver operating characteristic (ROC) curves, and tracking performance. The results show a significant benefit to using knowledge-aided processing based on multiple CPI clutter reflectivity maps.

Bios

Douglas Page received his Ph.D. in theoretical physics from Rensselaer Polytechnic Institute in 1992. From 1993-2000 he was with Technology Service Corporation in Trumbull, CT, working on a variety of problems in radar simulation and algorithm development. From 2000-2002, he was with the MITRE Corporation, where he continued work in radar signal processing including target detection in SAR imagery. In November, 2002 he joined ALPHATECH, where has been developing space-time adaptive processing (STAP) techniques for three different programs. Dr. Page is a member of Tau Beta Pi, Eta Kappu Nu, and Sigma Xi.

Mr. Gregory Owirka - ALPHATECH, Inc.

Mr. Gregory J. Owirka received the B.S. degree (1987) from Southeastern Massachusetts University in applied mathematics and the M.S. degree (1999) from the Northeastern University in Electrical Engineering. From 1987 to 2002, he worked at MIT Lincoln Laboratory as a technical staff member, developing algorithms and performing data analysis in the area of synthetic aperture radar (SAR) detection, discrimination, and classification. Mr. Owirka worked on a team that developed the first end-to-end ATR system, specifically designed to exploit high-resolution, fully polarimetric SAR imagery. He developed many of the core algorithms for the Army's fielded SAIP (Semi-Automated IMINT Processing) automatic target cueing (ATC) system. This development work included a multi-stage, template-based recognition system that used super-resolved SAR imagery to enhance recognition performance. From 2002 to the present, Mr. Owirka works at ALPHATECH Inc., where he is the section leader of the moving target technologies (MTT) section. Mr. Owirka has published extensively in the areas of airborne radar surveillance, automatic target recognition, and sensor exploitation.