Loading

Direction of Arrival Estimation on the Performance of WCMSR Technique
Niharika Mehta1, Romika Choudhary2

1Niharika Mehta, Department of Electronics & Communications, MRI University, Faridabad (Haryana), India.
2Romika Choudhary, Assistant Professor, Department of Electronics & Communications, MRI University, Faridabad (Haryana), India.
Manuscript received on 12 June 2014 | Revised Manuscript received on 19 June 2014 | Manuscript Published on 30 June 2014 | PP: 48-51 | Volume-4 Issue-1, June 2014 | Retrieval Number: A1704064114/14©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: This paper presents direction-of-arrival (DOA) estimation of wideband signals, and wideband covariance matrix sparse representation (W-CMSR) method is proposed. In W-CMSR, covariance matrix is taken such that the lower left triangular elements are aligned to form a new measurement vector. In W-CMSR technique we use constraint of sparsity, sparse representations are those representations that account for most or all information of a signal with a linear combination of a small number of elementary signals called atoms. Often the atoms are chosen from a so called over-complete dictionary. It means that given a signal firstly we form the dictionary which contains the atoms that represent the signal and then after that we find the smallest set of atoms from the dictionary to represent the signal. No prior information of the incident signal is required in W-CMSR, and no decomposition is done. Half-wavelength spacing restriction can be changed from the highest to the lowest frequency of the incident wideband signals.
Keywords: Direction-Of-Arrival (DOA) Estimation, Over Complete Representation, Sparse Representation, Wideband Signal, Source Localization.

Scope of the Article: Measurement & Performance Analysis