MSM-FOCUSS for distributed compressive sensing and wideband DOA estimation

Author

Huiping Duan

Author_Institution

Sch. of Electron. Eng., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

fYear

2014

fDate

20-23 Aug. 2014

Firstpage

400

Lastpage

403

Abstract

In order to recover an ensemble of signals which share a common sparsity pattern while being measured under different sensing matrices, we explore the MSM-FOCUSS algorithm by extending the well-known M-FOCUSS (FOCal Under-determined System Solver) approach from the MMV (Multiple-Measurement-Vectors) to the MSM (Multiple-Sensing-Matrices) scenario. The convergence of the algorithm, the sparsity of the solution and the uniqueness condition for the MSM problem are analyzed. The performance is demonstrated by examples of joint sparse representation in distributed compressive sensing and wideband DOA (Direction-Of-Arrival) estimation.

Keywords

compressed sensing; direction-of-arrival estimation; matrix algebra; signal representation; MMV; MSM; MSM-FOCUSS algorithm; direction-of-arrival estimation; distributed compressive sensing; ensemble signal recovery; focal underdetermined system solver approach; joint sparse representation; multiple measurement-vectors; multiple-sensing-matrices; wideband DOA estimation; Direction-of-arrival estimation; Estimation; Sensors; Signal processing algorithms; Sparse matrices; Vectors; Wideband; FOCUSS; distributed compressive sensing; multiple sensing matrices; sparse representation; wideband DOA estimation;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Signal Processing (DSP), 2014 19th International Conference on

Conference_Location

Hong Kong

Type

conf

DOI

10.1109/ICDSP.2014.6900694

Filename

6900694