TY - JOUR
T1 - Nonambiguous SAR Image Formation of Maritime Targets Using Weighted Sparse Approach
AU - Xu, Gang
AU - Xia, Xiang Gen
AU - Hong, Wei
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2018/3
Y1 - 2018/3
N2 - For a single-channel synthetic aperture radar (SAR), finite-pulse repetition frequency and nonideal antenna pattern cause azimuth ambiguities, i.e., ghosts in image domain. In this paper, a novel algorithm of locating processing weighted group lasso SAR image formation for maritime targets is proposed to effectively mitigate the ambiguities, which can work on a single-look complex SAR image. In the scheme, the ambiguous signal model using the conventional SAR focusing processor is first explicitly derived, showing the analytical expression of SAR image formulation. The weighted sparse group lasso algorithm is then employed to group-sparsely reconstruct the subimages of nonambiguous and ambiguous Doppler components. In particular, we introduce adaptively weighted sparsity constraint, obtained from a priori azimuth antenna pattern, and clutter clustering during sparse imaging. It should be emphasized that the proposed algorithm can effectively improve the azimuth resolution by coherently integrating the ambiguous signal components, which greatly helps the target detection and recognition in maritime surveillance. Finally, experiments based on simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.
AB - For a single-channel synthetic aperture radar (SAR), finite-pulse repetition frequency and nonideal antenna pattern cause azimuth ambiguities, i.e., ghosts in image domain. In this paper, a novel algorithm of locating processing weighted group lasso SAR image formation for maritime targets is proposed to effectively mitigate the ambiguities, which can work on a single-look complex SAR image. In the scheme, the ambiguous signal model using the conventional SAR focusing processor is first explicitly derived, showing the analytical expression of SAR image formulation. The weighted sparse group lasso algorithm is then employed to group-sparsely reconstruct the subimages of nonambiguous and ambiguous Doppler components. In particular, we introduce adaptively weighted sparsity constraint, obtained from a priori azimuth antenna pattern, and clutter clustering during sparse imaging. It should be emphasized that the proposed algorithm can effectively improve the azimuth resolution by coherently integrating the ambiguous signal components, which greatly helps the target detection and recognition in maritime surveillance. Finally, experiments based on simulated and measured data are performed to confirm the effectiveness of the proposed algorithm.
KW - Azimuth ambiguities
KW - Clutter clustering
KW - Sparse group lasso algorithm
KW - Synthetic aperture radar (SAR)
KW - Weighted sparsity constraint
UR - http://www.scopus.com/inward/record.url?scp=85033730354&partnerID=8YFLogxK
U2 - 10.1109/TGRS.2017.2763147
DO - 10.1109/TGRS.2017.2763147
M3 - Article
AN - SCOPUS:85033730354
SN - 0196-2892
VL - 56
SP - 1454
EP - 1465
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
IS - 3
ER -