Microlocal ISAR for Low Signal-to-Noise Environments

Abstract

The problem of extracting radar target information from multi-aspect high-range-resolution data is examined. We suggest a new non-imaging approach that is based on microlocal analysis, which is a mathematical theory developed to handle highfrequency asymptotics. In essence, we relate features of the target to high-frequency components of the data. To deal with realistic band-limited data, we propose an iterative algorithm (based on the generalized Radon-Hough transform) in which we estimate the high-frequency features of the data, one after another, and subtract out the corresponding band-limited components. The algorithm has been successfully tested on noisy data, and may have a number of advantages over conventional imaging methods.This work was supported by the Office of Naval Research. M.C. also thanks Gary Hewer and the ASEE Summer Faculty Research Program for supporting her stay at China Lake