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Beamforming for Direction-of-Arrival (DOA) Estimation-A Survey

by V Krishnaveni, T Kesavamurthy, Aparna. B
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 11
Year of Publication: 2013
Authors: V Krishnaveni, T Kesavamurthy, Aparna. B
10.5120/9970-4758

V Krishnaveni, T Kesavamurthy, Aparna. B . Beamforming for Direction-of-Arrival (DOA) Estimation-A Survey. International Journal of Computer Applications. 61, 11 ( January 2013), 4-11. DOI=10.5120/9970-4758

@article{ 10.5120/9970-4758,
author = { V Krishnaveni, T Kesavamurthy, Aparna. B },
title = { Beamforming for Direction-of-Arrival (DOA) Estimation-A Survey },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 11 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 4-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number11/9970-4758/ },
doi = { 10.5120/9970-4758 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:08:49.055973+05:30
%A V Krishnaveni
%A T Kesavamurthy
%A Aparna. B
%T Beamforming for Direction-of-Arrival (DOA) Estimation-A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 11
%P 4-11
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Direction-of-Arrival (DOA) estimation plays a vital role in many applications. Beamforming is the most prominent technique to estimate DOA. In this survey, a study of various beamforming techniques and algorithms to estimate the direction of arrival of a signal is made. An assessment on the background robust algorithms using Nyquist sampling rate and its Compressive sensing alternative is done. It is known that Bearing estimation algorithms obtain only a small number of direction of arrivals (DOAs) within the entire angle domain, when the sources are spatially sparse. Hence, it may be concluded that, the methods those specifically exploits this spatial sparsity property is advantageous. These methods use a very small number of measurements in the form of random projections of the sensor data along with one full waveform recording at one of the sensors.

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Index Terms

Computer Science
Information Sciences

Keywords

Beamforming Direction-of-Arrival Array processing MVDR MUSIC Root-MUSIC ESPRIT Spatial sparsity Compressive Sensing

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