TY - GEN
T1 - Wideband Interference Suppression for SAR by Time-Frequency-Pulse Joint Domain Processing
AU - Su, Jia
AU - Li, Haojiang
AU - Tao, Mingliang
AU - Fan, Yifei
AU - Wang, Ling
AU - Tao, Haihong
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/9/26
Y1 - 2020/9/26
N2 - Wide-band interference (WBI) is a critical issue for synthetic aperture radar (SAR), which may severely affect the imaging quality of SAR systems. To suppress WBI effectively, a novel interference suppression algorithm based on robust principal component analysis (RPCA) in time-frequency-pulse (TF-P) domain is proposed. For SAR echoes in TF-P domain, there are two useful properties: 1) The TF characteristic of useful signal in adjacent pulse are similar, indicating that useful signal has low-rank property; 2) Due to its variation of position and sparsely distrusted in TF-P domain, WBI has sparse characteristic. According to these properties, RPCA method is applied to decompose the TF-P matrix into a low-rank matrix (i.e. useful signal) and a sparse matrix (i.e. WBI). Finally, the WBIs can be reconstructed and subtracted from the echoes to realize the interference suppression. The experimental results of simulated data demonstrate that the proposed algorithm not only can suppress interference effectively, but also preserve the useful information as much as possible.
AB - Wide-band interference (WBI) is a critical issue for synthetic aperture radar (SAR), which may severely affect the imaging quality of SAR systems. To suppress WBI effectively, a novel interference suppression algorithm based on robust principal component analysis (RPCA) in time-frequency-pulse (TF-P) domain is proposed. For SAR echoes in TF-P domain, there are two useful properties: 1) The TF characteristic of useful signal in adjacent pulse are similar, indicating that useful signal has low-rank property; 2) Due to its variation of position and sparsely distrusted in TF-P domain, WBI has sparse characteristic. According to these properties, RPCA method is applied to decompose the TF-P matrix into a low-rank matrix (i.e. useful signal) and a sparse matrix (i.e. WBI). Finally, the WBIs can be reconstructed and subtracted from the echoes to realize the interference suppression. The experimental results of simulated data demonstrate that the proposed algorithm not only can suppress interference effectively, but also preserve the useful information as much as possible.
KW - robust principal component analysis
KW - Synthetic aperture radar
KW - time-frequency-pulse domain
KW - wide-band interference
UR - http://www.scopus.com/inward/record.url?scp=85101983566&partnerID=8YFLogxK
U2 - 10.1109/IGARSS39084.2020.9323259
DO - 10.1109/IGARSS39084.2020.9323259
M3 - 会议稿件
AN - SCOPUS:85101983566
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3774
EP - 3777
BT - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Y2 - 26 September 2020 through 2 October 2020
ER -