Sparse Auto-Calibration for Radar Coincidence Imaging with Gain-Phase Errors

Sensors

Xiaoli Zhou¹  Hongqiang Wang²  Yongqiang Cheng²  Yuliang Qin² 

[1] School of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;

关键词: radar coincidence imaging (RCI);    sparse recovery;    orthogonal matching pursuit (OMP);    gain-phase error;    auto-calibration;   

DOI  :  10.3390/s151127611

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.