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.