A Multiple Measurement Vector Approach for DOA Estimation

Title:A Multiple Measurement Vector Approach for DOA Estimation

Volume: 10 Issue: 3

Author(s): Seyyed Moosa Hosseini*Ramezan A. Sadeghzadeh

Affiliation:

• Faculty of Electrical Engineering, K.N. Toosi University of Technology, Tehran,Iran

Keywords: Compressed sensing, direction of arrival, multiple measurement vector, non-uniform linear array, novel algorithm, signal processing.

Abstract: Background: Compressed Sensing (CS) is an emerging signal processing technique for signal acquisition and reconstruction which recently finds applications in array processing. Direction of Arrival (DOA) is a well-known problem in array signal processing which can be treated with methods based on compressed sensing.

Methods: In this work, a novel algorithm has been developed based on sparse multiple measurement vector model (MMV) to estimate DOAs of far-field and narrowband sources in linear arrays scenarios. The proposed algorithm exploits singular value decomposition denoising to enhance the reconstruction process.

Conclusion: Several simulations have been carried out to show the superior performance of proposed method in comparison to simultaneous orthogonal matching pursuit (S-OMP), Ι2,1 minimization and root-MUISC in both uniform linear array (ULA) and nonuniform linear array (NLA) scenarios.

Cite this article as:

Hosseini Moosa Seyyed *, Sadeghzadeh A. Ramezan , A Multiple Measurement Vector Approach for DOA Estimation, Recent Advances in Electrical & Electronic Engineering 2017; 10 (3) . https://dx.doi.org/10.2174/2352096510666170601092534

DOI https://dx.doi.org/10.2174/2352096510666170601092534	Print ISSN 2352-0965
Publisher Name Bentham Science Publisher	Online ISSN 2352-0973