TY - GEN
T1 - Adaptive noise depression CSISAR imaging via OMP with CFAR thresholding
AU - Bu, Hong Xia
AU - Bai, Xia
AU - Zhao, Juan
AU - Song, Yu E.
AU - Yan, Ruo Ying
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/11/1
Y1 - 2016/11/1
N2 - Compressed sensing (CS)-based inverse synthetic aperture radar (ISAR) imaging with limited pulses performs well in the case of high signal-to-noise ratios. However, strong noise are usually inevitable in radar imaging, which challenges the CS-based approach. In this paper, we present an adaptive noise depression CS-ISAR imaging algorithm, which is based on constant false alarm rate (CFAR). Firstly, the noise level is estimated from the noise range cells which are discriminated by energy thresholding. Then the ISAR images are reconstructed via orthogonal matched pursuit (OMP), in which the iteration is terminated by a preseted residual thresholding (RT). The RT is set according to the estimated noise level for a certain CFAR. Experiments verify the efficiency of the proposed method.
AB - Compressed sensing (CS)-based inverse synthetic aperture radar (ISAR) imaging with limited pulses performs well in the case of high signal-to-noise ratios. However, strong noise are usually inevitable in radar imaging, which challenges the CS-based approach. In this paper, we present an adaptive noise depression CS-ISAR imaging algorithm, which is based on constant false alarm rate (CFAR). Firstly, the noise level is estimated from the noise range cells which are discriminated by energy thresholding. Then the ISAR images are reconstructed via orthogonal matched pursuit (OMP), in which the iteration is terminated by a preseted residual thresholding (RT). The RT is set according to the estimated noise level for a certain CFAR. Experiments verify the efficiency of the proposed method.
KW - Compressed sensing (CS)
KW - constant false alarm rate (CFAR)
KW - inverse synthetic aperture radar (ISAR)
KW - orthogonal matched pursuit (OMP)
UR - http://www.scopus.com/inward/record.url?scp=85007425823&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2016.7730302
DO - 10.1109/IGARSS.2016.7730302
M3 - Conference contribution
AN - SCOPUS:85007425823
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 4992
EP - 4995
BT - 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
Y2 - 10 July 2016 through 15 July 2016
ER -