Vector Extrapolation Based Fast Split Bregman Algorithm for Radar Forward-looking Imaging

Conventional split Bregman algorithm (SBA) has been used for improving the azimuth resolution for radar forward-looking imaging. However its convergence speed is not satisfactory. In this paper, a vector extrapolation based fast SBA (VEFSBA) is presented to accelerate the convergence of traditional SBA and improve azimuth resolution of radar forward-looking imaging. Based on the principle of vector extrapolation, the proposed VEFSBA adopts the second-order vector extrapolation strategy to reduce the number of iterations of traditional SBA. It not only effectively improves the azimuth resolution of radar forward-looking imaging, but also greatly reduces the number of iterations compared with the traditional SBA. Simulation and measured data are presented to demonstrate the superior performance of the proposed VEFSBA.

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