Radar Imaging and Feature Extraction
Final rept. 1996-1999
FLORIDA UNIV GAINESVILLE DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
Pagination or Media Count:
Advanced spectral estimation methods are presented for radar imaging and target feature extraction. We study problems involved in inverse synthetic aperture radar ISAR autofocus and imaging, synthetic aperture radar SAR autofocus and motion compensation, superresolution SAR image formation, three-dimensional 3-D target feature extraction via curvilinear SAR CLSAR, and time delay estimation. For the ISAR imaging problem, we present a parametric AUTOCLEAN AUTOfocus via CLEAN algorithm, and two non-parametric algorithms including an adaptive Capon and a recursive APES Amplitude and Phase EStimation. For the problems related to SAR imaging, we propose a Semi-PARametric SPAR algorithm for target feature extraction and superresolution image formation, and two parametric methods, MCRELAX Motion Compensation RELAX and MCCLEAN Motion Compensation CLEAN, for simultaneous target feature extraction and cross-range phase error compensation. For the 3-D target feature extraction problem, an AUTOfocus algorithm based on the RELAXation-based optimization approach AUTORELAX is proposed to compensate the aperture errors in CLSAR and to extract 3-D target features. For the time delay estimation problem, we first present a Weighted Fourier transform and RELAXation-based WRELAX approach. Then, a MODE-WRELAX MODE Method Of Direction Estimation together with WRELAX algorithm is proposed for the superresolution time delay estimation.
- Active and Passive Radar Detection and Equipment