caa a22 4500 606206183 CHVBK 20210128101010.0 cr unu---uuuuu 210128e20150801xx s 000 0 eng 10.1007/s00034-015-9974-y doi (NATIONALLICENCE)springer-10.1007/s00034-015-9974-y Synthetic Aperture Radar Imaging Using Basis Selection Compressed Sensing [Elektronische Daten] [Dongjie Bi, Yongle Xie, Yahong Zheng] A compressed sensing method with basis selection is applied to a millimeter-wave synthetic aperture radar (SAR) imaging system. With a large candidate set of bases to choose from and without any a priori knowledge of the proper basis, the proposed method selects the sparsifying basis during the first few iterations of the L1 optimization according to the information from incomplete measurements and the coherence between the measurement matrix and sparsifying matrices. Several decision metrics can be used to select the basis, including the impulsiveness and Gini index of the available image at the current iteration. The proposed method is tested on two examples: a simulated image and its SAR measurement, and an experimental measurement obtained at 150GHz via roaster scanning. The results from the simulation and experiment indicate that the proposed algorithm can always find a very good basis from the set of over 270 bases within the first two to five iterations of the L1 optimization. Springer Science+Business Media New York, 2015 Basis selection nationallicence Best basis nationallicence Compressed sensing nationallicence Synthetic aperture radar imaging nationallicence Bi Dongjie School of Automation Engineering, University of Electronic Science and Technology of China, 611731, Chengdu, People's Republic of China aut Xie Yongle School of Automation Engineering, University of Electronic Science and Technology of China, 611731, Chengdu, People's Republic of China aut Zheng Yahong Department of Electrical and Computer Engineering, Missouri University of Science and Technology, 65409, Rolla, MO, USA aut Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2561-2576 0278-081X 34:8<2561 2015 34 34 https://doi.org/10.1007/s00034-015-9974-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00034-015-9974-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Bi Dongjie School of Automation Engineering, University of Electronic Science and Technology of China, 611731, Chengdu, People's Republic of China aut NATIONALLICENCE 700 1- Xie Yongle School of Automation Engineering, University of Electronic Science and Technology of China, 611731, Chengdu, People's Republic of China aut NATIONALLICENCE 700 1- Zheng Yahong Department of Electrical and Computer Engineering, Missouri University of Science and Technology, 65409, Rolla, MO, USA aut NATIONALLICENCE 773 0- Circuits, Systems, and Signal Processing Springer US; http://www.springer-ny.com 34/8(2015-08-01), 2561-2576 0278-081X 34:8<2561 2015 34 34