TY - GEN
T1 - L1/2 regularization based azimuth resolution enhancement for multi-channel radar forward-looking imaging
AU - Sun, Jinping
AU - Zhang, Xuwang
AU - Zhou, Rui
AU - Fu, Jinbin
AU - Wang, Jun
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - When the airborne or missile borne radar works at the forward-looking imaging mode, the common techniques for improving azimuth resolution are invalid, because the difference between the Doppler frequencies of targets in different azimuths is very small. Meanwhile, other real beam sharpening methods only have very limited effect on azimuth resolution enhancement. For the problem of forward-looking imaging of ship targets at sea surface, a L1/2 regularization based azimuth resolution enhancement algorithm is proposed in this paper. This algorithm can make full use of the obvious sparsity in the imaging area. The linear observation signal model for forward-looking imaging is built, and the iterative calculation process of L1/2 regularization and the detailed steps of multi-channel radar forward-looking imaging are provided in this paper. Finally, the effectiveness of the proposed algorithm is tested and verified with simulation data and real data.
AB - When the airborne or missile borne radar works at the forward-looking imaging mode, the common techniques for improving azimuth resolution are invalid, because the difference between the Doppler frequencies of targets in different azimuths is very small. Meanwhile, other real beam sharpening methods only have very limited effect on azimuth resolution enhancement. For the problem of forward-looking imaging of ship targets at sea surface, a L1/2 regularization based azimuth resolution enhancement algorithm is proposed in this paper. This algorithm can make full use of the obvious sparsity in the imaging area. The linear observation signal model for forward-looking imaging is built, and the iterative calculation process of L1/2 regularization and the detailed steps of multi-channel radar forward-looking imaging are provided in this paper. Finally, the effectiveness of the proposed algorithm is tested and verified with simulation data and real data.
KW - Compressive sensing
KW - Forward-looking imaging
KW - L regularization
KW - multi-channel radar
UR - https://www.scopus.com/pages/publications/85041838513
U2 - 10.1109/IGARSS.2017.8127648
DO - 10.1109/IGARSS.2017.8127648
M3 - 会议稿件
AN - SCOPUS:85041838513
T3 - International Geoscience and Remote Sensing Symposium (IGARSS)
SP - 3074
EP - 3077
BT - 2017 IEEE International Geoscience and Remote Sensing Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Y2 - 23 July 2017 through 28 July 2017
ER -