TY - GEN
T1 - ISAR imaging using parametric L 0-norm minimization
AU - Li, Gang
AU - Wang, Xiqin
AU - Xia, Xiang Gen
PY - 2012
Y1 - 2012
N2 - We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by parametric L 0-norm minimization, which ensures the sparsest ISAR image.
AB - We present a sparsity-driven algorithm of inverse synthetic aperture radar (ISAR) imaging. Based on the parametric sparse representation of the received ISAR signal, the problem of ISAR image formation is converted into the joint estimation of the target rotation rate and the sparse power distribution in the spatial domain. This goal is achieved by parametric L 0-norm minimization, which ensures the sparsest ISAR image.
UR - http://www.scopus.com/inward/record.url?scp=84864272369&partnerID=8YFLogxK
U2 - 10.1109/RADAR.2012.6212177
DO - 10.1109/RADAR.2012.6212177
M3 - Conference contribution
AN - SCOPUS:84864272369
SN - 9781467306584
T3 - IEEE National Radar Conference - Proceedings
SP - 421
EP - 424
BT - 2012 IEEE Radar Conference
T2 - 2012 IEEE Radar Conference: Ubiquitous Radar, RADARCON 2012
Y2 - 7 May 2012 through 11 May 2012
ER -