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.
X. Yang et al., "Microwave Synthetic Aperture Radar Imaging using Sparse Measurement," Proceedings of the IEEE International Instrumentation and Measurement Technology Conference (20166, Taipei, Taiwan), vol. 2016-July, Institute of Electrical and Electronics Engineers (IEEE), May 2016.
The definitive version is available at https://doi.org/10.1109/I2MTC.2016.7520526
IEEE International Instrumentation and Measurement Technology Conference (2016: May 23-26, Taipei, Taiwan)
Electrical and Computer Engineering
Keywords and Phrases
Compressed Sensing; Synthetic Aperture Radar; Digital Signal Processing; Image Processing; Image Quality; Radar Imaging; Radar Signal Processing; Signal Reconstruction; Different Densities; Image Recovery; Measurement Time; Measurements Of; Sparse Sampling; Spatial Measurements; Wideband Microwaves
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Article - Conference proceedings
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01 May 2016