Sparse Auto-Calibration for Radar Coincidence Imaging with Gain-Phase ErrorsReport as inadecuate




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School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China





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Academic Editor: Assefa M. Melesse

Abstract Radar coincidence imaging RCI is a high-resolution staring imaging technique without the limitation of relative motion between target and radar. The sparsity-driven approaches are commonly used in RCI, while the prior knowledge of imaging models needs to be known accurately. However, as one of the major model errors, the gain-phase error exists generally, and may cause inaccuracies of the model and defocus the image. In the present report, the sparse auto-calibration method is proposed to compensate the gain-phase error in RCI. The method can determine the gain-phase error as part of the imaging process. It uses an iterative algorithm, which cycles through steps of target reconstruction and gain-phase error estimation, where orthogonal matching pursuit OMP and Newton’s method are used, respectively. Simulation results show that the proposed method can improve the imaging quality significantly and estimate the gain-phase error accurately. View Full-Text

Keywords: radar coincidence imaging RCI; sparse recovery; orthogonal matching pursuit OMP; gain-phase error; auto-calibration radar coincidence imaging RCI; sparse recovery; orthogonal matching pursuit OMP; gain-phase error; auto-calibration





Author: Xiaoli Zhou * , Hongqiang Wang, Yongqiang Cheng and Yuliang Qin

Source: http://mdpi.com/



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