论文信息 - An Accelerated Iterative Shrinkage-Thresholding Algorithm for Real-Beam Scanning Radar Super-Resolution

An Accelerated Iterative Shrinkage-Thresholding Algorithm for Real-Beam Scanning Radar Super-Resolution

Iterative shrinkage-thresholding algorithm (ISTA) is a simple and robust method to realize super-resolution of real-beam scanning radar. However, slow convergence is a drawback. This work proposes an accelerated iterative shrinkage-thresholding algorithm based on Taylor series expansion. Simulation results are presented to validate the effectiveness the validity and high efficiency of the proposed algorithm.

[1] Marc Teboulle,et al. A fast Iterative Shrinkage-Thresholding Algorithm with application to wavelet-based image deblurring , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[2] D. Russell Luke,et al. Finding Best Approximation Pairs Relative to a Convex and Prox-Regular Set in a Hilbert Space , 2008, SIAM J. Optim..

[3] Mário A. T. Figueiredo,et al. Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems , 2007, IEEE Journal of Selected Topics in Signal Processing.

[4] K. Bredies,et al. Iterative soft-thresholding converges linearly , 2007 .

[5] Jianyu Yang,et al. Angular resolution enhancement of real-beam scanning radar base on accelerated iterative shinkage/thresholding algorithm , 2016, 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

[6] Yue Wang,et al. Real-beam scanning radar angular super-resolution via sparse deconvolution , 2014, 2014 IEEE Geoscience and Remote Sensing Symposium.

[7] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..