Microlocal ISAR for Low Signal-to-Noise Environments
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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.