TY - GEN
T1 - Modified Enlcs Method with Low Complexity for Highly Squint Sar Imaging
AU - Liu, Qian
AU - Wei, Feiming
AU - Hai, Yu
AU - Li, Junao
AU - Yang, Qing
AU - Li, Zhongyu
AU - Wu, Junjie
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - In recent years, many imaging algorithms for highly squint synthetic aperture radar (SAR) have been proposed. An algorithm based on keystone transform (KT) and azimuth Extended Nonlinear Chirp Scaling (ENLCS) is widely used in highly squint SAR imaging processing. It's effective in solving spatial-variant linear range cell migration (LRCM) and azimuth-variant Doppler parameters. However, due to the highly squint configuration, the beam center crossing time of many illuminated targets are not included in the track. We need extend the azimuth data length to ensure the targets a corresponding position in the data, which leads to an increase in computational complexity. And the imaging result also has geometric distortion. This paper proposes an improved ENLCS method with lower complexity combined with fast KT. First, we use the low complexity KT without interpo-lation in the RCM correction (RCMC) process. Then, we find a solution to reduce the extended data length by adding a time shift factor in the ENLCS process, saving data storage space and operation cost. Finally, geometric correction is performed by the grid mapping. The effectiveness of the proposed method is verified by numerical simulation and real data processing.
AB - In recent years, many imaging algorithms for highly squint synthetic aperture radar (SAR) have been proposed. An algorithm based on keystone transform (KT) and azimuth Extended Nonlinear Chirp Scaling (ENLCS) is widely used in highly squint SAR imaging processing. It's effective in solving spatial-variant linear range cell migration (LRCM) and azimuth-variant Doppler parameters. However, due to the highly squint configuration, the beam center crossing time of many illuminated targets are not included in the track. We need extend the azimuth data length to ensure the targets a corresponding position in the data, which leads to an increase in computational complexity. And the imaging result also has geometric distortion. This paper proposes an improved ENLCS method with lower complexity combined with fast KT. First, we use the low complexity KT without interpo-lation in the RCM correction (RCMC) process. Then, we find a solution to reduce the extended data length by adding a time shift factor in the ENLCS process, saving data storage space and operation cost. Finally, geometric correction is performed by the grid mapping. The effectiveness of the proposed method is verified by numerical simulation and real data processing.
KW - Chirp-z transform
KW - Geometric correction
KW - Keystone transform
KW - Range cell migration correction
UR - https://www.scopus.com/pages/publications/85140411536
U2 - 10.1109/IGARSS46834.2022.9883170
DO - 10.1109/IGARSS46834.2022.9883170
M3 - 会议稿件
AN - SCOPUS:85140411536
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 2514
EP - 2517
BT - IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2022
Y2 - 17 July 2022 through 22 July 2022
ER -