Wavelets feature aided tracking (WFAT) using GMTI/HRR data

This paper presents a research development of wavelets feature aided tracking, which effectively combines information from both high-resolution range (HRR) radar profiles and ground moving target indication (GMTI) radar reports. The state-of-the-art wavelets-based statistical signal processing technique: wavelets domain hidden Markov trees is used to extract robust features from HRR profiles. With the assistance of HRR wavelets features, a GMTI tracker based on a probabilistic data association logic can effectively track ground moving targets in confusing scenarios. (C) 2003 Elsevier B.V. All rights reserved.