Advanced compressed sensing approach to synthesis of sparse antenna arrays

Huan Wang; Yibin Rui; Zeyu Sun; Renhong Xie; Peng Li; Ning Lv

doi:10.1117/12.2559148

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31 December 2019 Advanced compressed sensing approach to synthesis of sparse antenna arrays

Huan Wang; Yibin Rui; Zeyu Sun; Renhong Xie; Peng Li; Ning Lv

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Proceedings Volume 11384, Eleventh International Conference on Signal Processing Systems; 113840U (2019) https://doi.org/10.1117/12.2559148
Event: Eleventh International Conference on Signal Processing Systems, 2019, Chengdu, China

Abstract

As an effective method in signal reconstruction model, compressed sensing (CS) has achieved excellent performance in sparse array reconstruction. However, it is necessary to set the penalization factor before iterative calculation, which will increase the difficulty to convergence the result to the global optimal solution. In this paper, we remove the process of choosing penalization factor and reconstruction error by modifying the iterative expression as well as alternating direction method of multipliers (ADMM) algorithm respectively. In addition, the improved model is shown to be convex and thus can be solved using the CVX toolbox. Simulation result shows that the reference pattern could be reconstructed with minimum number of antenna elements by the proposed algorithms. Moreover, the proposed methods have significant performance improvement in main sidelobe level (MSL).

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Huan Wang, Yibin Rui, Zeyu Sun, Renhong Xie, Peng Li, and Ning Lv "Advanced compressed sensing approach to synthesis of sparse antenna arrays", Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113840U (31 December 2019); https://doi.org/10.1117/12.2559148

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KEYWORDS

Antennas

Compressed sensing

Process modeling

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