%0 Journal Article
%T Translational motion compensation for ISAR imaging under low SNR by minimum entropy
%A Lei Zhang
%A Jia-lian Sheng
%A Jia Duan
%A Meng-dao Xing
%A Zhi-jun Qiao and Zheng Bao
%J EURASIP Journal on Advances in Signal Processing
%D 2013
%I 
%R 10.1186/1687-6180-2013-33
%X In general, conventional error correction for inverse synthetic aperture radarimaging consists of range alignment and phase adjustment, which compensate range shift and phase error, respectively. Minimum entropy-based methods have been proposed to realize range alignment and phase adjustment. However, it becomes challenging to align high-resolution profiles when strong noise presents, even using entropy minimization. Consequently, the subsequent phase adjustment fails to correct phase errors. In this article, we propose a novel method for translational motion correction, where entropy minimization is utilized to achieve range alignment and phase adjustment jointly. And, a coordinate descent algorithm is proposed to solve the optimization implemented by quasi-Newton algorithm. Moreover, a method for coarse motion estimation is also proposed for initialization in solving the optimization. Both simulated and real-measured datasets are used to confirm the effectiveness of the joint motion correction in low signal-to-noise ratio situations.
%U http://asp.eurasipjournals.com/content/2013/1/33/abstract