Title :
Minimum Entropy via Subspace for ISAR Autofocus
Author :
Cao, Pan ; Xing, Mengdao ; Sun, Guangcai ; Li, Yachao ; Bao, Zheng
Author_Institution :
Key Lab. for Radar Signal Process., Xidian Univ., Xi´´an, China
Abstract :
In this letter, a novel approach to autofocus for inverse synthetic aperture radar (ISAR) imaging called minimum entropy via subspace autofocus is presented. This scheme uses the weighted signal subspace to express the phase errors left in the echoes after range-bin alignment and estimates the optimal weights sequentially via an optimization algorithm based on an entropy minimization principle, and its robustness and convergence can be ensured by the optimization method. Both the theoretical analysis and processing results of the real ISAR data have confirmed the feasibility of this new scheme.
Keywords :
minimum entropy methods; radar imaging; remote sensing by radar; synthetic aperture radar; ISAR autofocus; ISAR imaging; entropy minimization principle; inverse synthetic aperture radar; minimum entropy via subspace; optimization algorithm; phase errors; range-bin alignment; weighted signal subspace; Array manifold; autofocus; inverse synthetic aperture radar (ISAR); minimum entropy; signal subspace;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2009.2031658