Translational motion compensation for ISAR imaging under low SNR by minimum entropy

• Published in: EURASIP journal on advances in signal processing Vol. 2013; no. 1; pp. 1 - 19
• Main Authors: Zhang, Lei, Sheng, Jia-lian, Duan, Jia, Xing, Meng-dao, Qiao, Zhi-jun, Bao, Zheng
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 22.02.2013; BioMed Central Ltd
• Subjects: Algorithms; Alignment; Compensation; Emerging Radar Techniques; Engineering; Entropy; Minimization; Optimization; Phase error; Quantum Information Technology; Signal,Image and Speech Processing; Spintronics; Translational motion; Range alignment; Phase adjustment; Inverse synthetic aperture radar (ISAR); Motion compensation; Minimum entropy; Low signal-to-noise ratio (low SNR)
• ISSN: 1687-6180; 1687-6172; 1687-6180
• DOI: 10.1186/1687-6180-2013-33

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.