Journal of Astronautics ›› 2012, Vol. 33 ›› Issue (5): 642-647.doi: 10.3873/j.issn.1000-1328.2012.05.017

• E&IE • Previous Articles     Next Articles

Sparse Signal Reconstruction Based on Iterative Smoothed l 0 Norm Minimization

WANG Jun-hua, HUANG Zhi-tao, ZHOU Yi-yu   

  1. (School of Electronic Science and Engineering, NUDT, Changsha 410073, China)
  • Received:2011-06-20 Revised:2011-12-02 Online:2012-05-15 Published:2012-05-11

Abstract: Compressed Sensing (CS) is a new framework for simultaneous sensing and compression, and how to reconstruct sparse signal form limited measurements is the key problem in CS. In this paper, a novel method called Iterative Smoothed l 0  -norm (ISL0) is proposed for sparse signal reconstruction. This method estimates a support set  I  from a current reconstruction and obtains a new reconstruction by solving the minimization problem based on the support set  I, and it iterates these two steps for a small number of times. Simulation results show that the proposed method needs fewer measurements than existing methods, while needing the low computational cost.

Key words: Compressed sensing, Sparse signal reconstruction, Basis pursuit, Smoothed , l 0 norm

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