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Journal of Applied Remote Sensing

Adaptive sparse reconstruction with joint parametric estimation for high-speed uniformly moving targets in coincidence imaging radar
Author(s): Guofeng Zha; Hongqiang Wang; Zhaocheng Yang; Yongqiang Cheng; Yuliang Qin
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Paper Abstract

As a complementary imaging technology, coincidence imaging radar (CIR) achieves high resolution for stationary or low-speed targets under the assumption of ignoring the influence of the original position mismatching. As to high-speed moving targets moving from the original imaging cell to other imaging cells during imaging, it is inaccurate to reconstruct the target using the previous imaging plane. We focus on the recovery problem for high-speed moving targets in the CIR system based on the intrapulse frequency random modulation signal in a single pulse. The effects induced by the motion on the imaging performance are analyzed. Because the basis matrix in the CIR imaging equation is determined by the unknown velocity parameter of the moving target, both the target images and basis matrix should be estimated jointly. We propose an adaptive joint parametric estimation recovery algorithm based on the Tikhonov regularization method to update the target velocity and basis matrix adaptively and recover the target images synchronously. Finally, the target velocity and target images are obtained in an iterative manner. Simulation results are presented to demonstrate the efficiency of the proposed algorithm.

Paper Details

Date Published: 2 May 2016
PDF: 18 pages
J. Appl. Remote Sens. 10(2) 025009 doi: 10.1117/1.JRS.10.025009
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Guofeng Zha, National Univ. of Defense Technology (China)
Hongqiang Wang, National Univ. of Defense Technology (China)
Zhaocheng Yang, Shenzhen Univ. (China)
Yongqiang Cheng, National Univ. of Defense Technology (China)
Yuliang Qin, National Univ. of Defense Technology (China)


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