Microwave synthetic aperture radar imaging using sparse measurement
This paper evaluates Compressed Sensing (CS) techniques for image recovery from sparse measurement of wideband microwave synthetic aperture radar. A specimen under test (SUT) consists of a tray of small rocks of different densities and with/without one piece that is wrapped in aluminum foil. The fully sampled measurements of the SUT are randomly under sampled in the space domain and the images are reconstructed from measurements of 10% 50% sparse sampling rates using conventional zero filling (ZF) and NUFFT methods in comparison to the advanced CS method. The results show that the CS method achieves good image quality with as low as 30% sparse sampling rate, while ZF and NUFFT require 50% to obtain acceptable quality. The reduction of spatial measurement leads to reduced cost or reduced measurement time.
2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings