Source localization using a sparse representation framework to achieve superresolution

Authors:
Xiansheng Guo;Qun Wan;Chunqi Chang;Edmund Y. Lam
Affiliations:
Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam, Hong Kong and Department of Electronic Engineering, University of Electronic Science and Technology of China ...;Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, People's Republic of China 610054;Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam, Hong Kong;Department of Electrical and Electronic Engineering, University of Hong Kong, Pokfulam, Hong Kong
Venue:
Multidimensional Systems and Signal Processing
Year:
2010

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Abstract

We present a source localization approach using resampling within a sparse representation framework. In particular, the amplitude and phase information of the sparse solution is considered holistically to estimate the direction-of-arrival (DOA), where a resampling technique is developed to determine which information will give a more precise estimation. The simulation results confirm the efficacy of our proposed method.