TY - JOUR
T1 - A novel tensor technique for simultaneous narrowband and wideband interference suppression on single-channel SAR system
AU - Huang, Yan
AU - Zhang, Lei
AU - Li, Jie
AU - Hong, Wei
AU - Nehorai, Arye
N1 - Funding Information:
Manuscript received March 19, 2019; revised May 20, 2019; accepted June 25, 2019. Date of publication August 21, 2019; date of current version November 25, 2019. This work was supported in part by the National Natural Science Foundation of China under Grant 61901112, Grant 61771372, Grant 61801297, and Grant 61701106, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20170698, and in part by the Shen-zhen University under Grant 2019119. (Corresponding authors: Yan Huang; Lei Zhang.) Y. Huang and W. Hong are with the State Key Laboratory of Millimeter Waves, Southeast University, Nanjing 210100, China, and also with the Research Institute of Millimeter Wave and Terahertz Technology, Nanjing 210100, China (e-mail: yellowstone0636@hotmail.com).
Publisher Copyright:
© 1980-2012 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Nowadays, in the electromagnetism environment, the complex interferences, including the narrowband interferences (NBIs) and wideband interferences (WBIs), may severely affect the imaging quality of synthetic aperture radar (SAR) systems. Most traditional methods can only tackle with one kind of isolated interferences, NBIs or WBIs, which are widely distributed in the 1-D range frequency domain or 2-D range time-frequency domain. In this paper, we propose a complex tensor robust principal component analysis (CT-RPCA) method based on a novel 3-D range-azimuth-space tensor model to mitigate continuously distributed NBIs and WBIs simultaneously. The main contributions of this paper are summarized in three aspects. First, we strictly prove the low-rank property of the isolated NBIs and WBIs in the range-azimuth domain. Second, we use multiple views of the signal to construct a novel 3-D range-azimuth-space tensor model, where both the NBI tensor and the WBI tensor have spatial low-rank property due to the approximately stable frequency bands along the spatial dimension. Third, the CT-RPCA method is employed to efficiently suppress NBIs and WBIs simultaneously by solving the tensor RPCA problem. Finally, the real SAR data with simulated complex interferences are employed to demonstrate the effectiveness of the proposed method.
AB - Nowadays, in the electromagnetism environment, the complex interferences, including the narrowband interferences (NBIs) and wideband interferences (WBIs), may severely affect the imaging quality of synthetic aperture radar (SAR) systems. Most traditional methods can only tackle with one kind of isolated interferences, NBIs or WBIs, which are widely distributed in the 1-D range frequency domain or 2-D range time-frequency domain. In this paper, we propose a complex tensor robust principal component analysis (CT-RPCA) method based on a novel 3-D range-azimuth-space tensor model to mitigate continuously distributed NBIs and WBIs simultaneously. The main contributions of this paper are summarized in three aspects. First, we strictly prove the low-rank property of the isolated NBIs and WBIs in the range-azimuth domain. Second, we use multiple views of the signal to construct a novel 3-D range-azimuth-space tensor model, where both the NBI tensor and the WBI tensor have spatial low-rank property due to the approximately stable frequency bands along the spatial dimension. Third, the CT-RPCA method is employed to efficiently suppress NBIs and WBIs simultaneously by solving the tensor RPCA problem. Finally, the real SAR data with simulated complex interferences are employed to demonstrate the effectiveness of the proposed method.
KW - Complex tensor robust principal component analysis (CT-RPCA)
KW - narrowband interference (NBI) suppression
KW - range-azimuth-space tensor model
KW - wideband interference (WBI) suppression
UR - http://www.scopus.com/inward/record.url?scp=85074186354&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2019.2927764
DO - 10.1109/TGRS.2019.2927764
M3 - Article
AN - SCOPUS:85074186354
SN - 0196-2892
VL - 57
SP - 9575
EP - 9588
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 12
M1 - 8809364
ER -