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http://dx.doi.org/10.6109/jkiice.2013.17.10.2252

Sparse Signal Recovery with Parallel Orthogonal Matching Pursuit for Multiple Measurement Vectors  

Park, Jeonghong (Department of Information and Communication Engineering, Gyeongsang National University)
Ban, Tae Won (Department of Information and Communication Engineering, Gyeongsang National University)
Jung, Bang Chul (Department of Information and Communication Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.17, no.10, 2013 , pp. 2252-2258 More about this Journal
Abstract
In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the simultaneous orthogonal matching pursuit (S-OMP) which has been widely used as a greedy algorithm for sparse signal recovery for multiple measurement vector (MMV) problem. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the first iteration, (2) the conventional S-OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP for MMV outperforms than the conventional S-OMP both in terms of exact recovery ratio (ERR) and mean-squared error (MSE).
Keywords
Compressed sensing; Sparse signal recovery; Simultaneous OMP; Multiple measurement vectors; Mean squared error;
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