Vector extrapolation accelerated iterative shrinkage/thresholding regularization method for forward-looking scanning radar super-resolution imaging

Ke Tan; Wenchao Li; Yulin Huang; Qian Zhang; Yongchao Zhang; Junjie Wu; Jianyu Yang

doi:10.1117/1.JRS.12.045016

11 December 2018 Vector extrapolation accelerated iterative shrinkage/thresholding regularization method for forward-looking scanning radar super-resolution imaging

Ke Tan, Wenchao Li, Yulin Huang, Qian Zhang, Yongchao Zhang, Junjie Wu, Jianyu Yang

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 4, 045016 (December 2018). https://doi.org/10.1117/1.JRS.12.045016

Abstract

The iterative shrinkage/thresholding regularization method is an efficient and robust approach to implement super-resolution imaging for forward-looking scanning radar (FLSR). Nevertheless, numerous iterations are normally required to obtain a high super-resolution ratio and thus it can be time consuming. A vector extrapolation accelerated iterative shrinkage/thresholding regularization method is proposed for FLSR. In order to achieve effective acceleration, a predicted point is particularly formulated by linearly extrapolating the historical iterates before conducting the iterative shrinkage/thresholding operation. To reduce the prediction error and stabilize the acceleration process, an adaptively adjusted acceleration step size is derived according to the similarity of the adjacent iterative vectors. Last, a fixed-threshold constraining operator is conducted on the step size to guarantee the convergence of the acceleration method. The results of simulation experiment and real data processing verify the advantage of the proposed method in both the convergence speed and super-resolution performance when compared with the traditional acceleration methods.

Citation Download Citation

Ke Tan, Wenchao Li, Yulin Huang, Qian Zhang, Yongchao Zhang, Junjie Wu, and Jianyu Yang "Vector extrapolation accelerated iterative shrinkage/thresholding regularization method for forward-looking scanning radar super-resolution imaging," Journal of Applied Remote Sensing 12(4), 045016 (11 December 2018). https://doi.org/10.1117/1.JRS.12.045016

Received: 5 December 2017; Accepted: 16 November 2018; Published: 11 December 2018

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