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Journal of Electronic Imaging • Open Access

Radar coincidence imaging with phase error using Bayesian hierarchical prior modeling
Author(s): Xiaoli Zhou; Hongqiang Wang; Yongqiang Cheng; Yuliang Qin

Paper Abstract

Radar coincidence imaging (RCI) is a high-resolution imaging technique without the limitation of relative motion between target and radar. In sparsity-driven RCI, the prior knowledge of imaging model requires to be known accurately. However, the phase error generally exists as a model error, which may cause inaccuracies of the model and defocus the image. The problem is formulated using Bayesian hierarchical prior modeling, and the self-calibration variational message passing (SC-VMP) algorithm is proposed to improve the performance of RCI with phase error. The algorithm determines the phase error as part of the imaging process. The scattering coefficient and phase error are iteratively estimated using VMP and Newton’s method, respectively. Simulation results show that the proposed algorithm can estimate the phase error accurately and improve the imaging quality significantly.

Paper Details

Date Published: 1 February 2016
PDF: 9 pages
J. Electron. Imag. 25(1) 013018 doi: 10.1117/1.JEI.25.1.013018
Published in: Journal of Electronic Imaging Volume 25, Issue 1
Show Author Affiliations
Xiaoli Zhou, National Univ. of Defense Technology (China)
Hongqiang Wang, National Univ. of Defense Technology (China)
Yongqiang Cheng, National Univ. of Defense Technology (China)
Yuliang Qin, National Univ. of Defense Technology (China)

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