TY - GEN
T1 - SAR Interference Suppression Based on Signal Synthesis from Joint Time-Frequency Distribution
AU - Su, Jia
AU - Tao, Mingliang
AU - Xie, Jian
AU - Wen, Cai
AU - Zheng, Guimei
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In synthetic aperture radar (SAR) system, the separation and reconstruction of useful signal from Narrow-band interference (NBI) and Wide-band interference (WBI) components is a challenging problem. In this paper, a novel time-varying interference suppression algorithm is proposed based on the signal synthesis from joint time-frequency (TF) distribution. This algorithm makes full use of two TF representations: Wigner distribution (WD) and cross WD (CWD). After cross-terms elimination, these two TF representations are equal or close to the sum of WDs or CWDs of individual signal components, respectively. Based on this property, interferences can be separated and reconstructed by matrix rearrangement and eigenvalue decomposition (EVD). Compared with the traditional SSM (TSSM), the proposed algorithm has two advantages: 1) it is more accurate, since it avoids the approximate interpolation to WD; 2) it is quite time-saving, due to its matrix obtained by fast Fourier transform (FFT) and matrix rearrangement instead of the discrete Fourier transform (DFT). Experimental results demonstrate the effectiveness of the proposed approach in terms of accuracy and computational complexity.
AB - In synthetic aperture radar (SAR) system, the separation and reconstruction of useful signal from Narrow-band interference (NBI) and Wide-band interference (WBI) components is a challenging problem. In this paper, a novel time-varying interference suppression algorithm is proposed based on the signal synthesis from joint time-frequency (TF) distribution. This algorithm makes full use of two TF representations: Wigner distribution (WD) and cross WD (CWD). After cross-terms elimination, these two TF representations are equal or close to the sum of WDs or CWDs of individual signal components, respectively. Based on this property, interferences can be separated and reconstructed by matrix rearrangement and eigenvalue decomposition (EVD). Compared with the traditional SSM (TSSM), the proposed algorithm has two advantages: 1) it is more accurate, since it avoids the approximate interpolation to WD; 2) it is quite time-saving, due to its matrix obtained by fast Fourier transform (FFT) and matrix rearrangement instead of the discrete Fourier transform (DFT). Experimental results demonstrate the effectiveness of the proposed approach in terms of accuracy and computational complexity.
KW - Cross - Wigner distribution
KW - Signal synthesis
KW - Wigner distribution
UR - http://www.scopus.com/inward/record.url?scp=85077684209&partnerID=8YFLogxK
U2 - 10.1109/IGARSS.2019.8898700
DO - 10.1109/IGARSS.2019.8898700
M3 - 会议稿件
AN - SCOPUS:85077684209
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2383
EP - 2386
BT - 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019
Y2 - 28 July 2019 through 2 August 2019
ER -