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Prior-Exploiting Direction-of-Arrival Algorithm For Partially Uncorrelated Source Signals
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0001-6615-6583
KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.ORCID iD: 0000-0002-6855-5868
University of Lyon, University of Saint Etienne, LASPI.
2013 (English)In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE conference proceedings, 2013, 3972-3976 p.Conference paper, Published paper (Refereed)
Abstract [en]

In certain direction-of-arrival (DOA) estimation scenarios some of the source directions are known to the operator even before measurements are acquired. It is then undesirable to use regular DOA-algorithms which waste data-samples estimating the known directions. Additionally, in some applications it is known that the signals emanating from the known directions are uncorrelated with those coming from the unknown directions. In this article we present a novel algorithm which exploits the combination of such prior knowledge in a manner more efficient (in terms of accuracy) than any algorithm known to the authors. Through numerical Monte-Carlo simulations we show the estimator to attain the theoretical accuracy bound for significantly lower signal-to-noise ratios than current state-of-the-art methods. Additionally we show the proposed algorithm to treat the stricter problem of entirely uncorrelated emitters better than current state of the art. 

Place, publisher, year, edition, pages
IEEE conference proceedings, 2013. 3972-3976 p.
Series
IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedings, ISSN 1520-6149
Keyword [en]
Accuracy, Arrays, Covariance matrix, Direction of arrival estimation, Signal processing algorithms
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-122178DOI: 10.1109/ICASSP.2013.6638404ISI: 000329611504026Scopus ID: 2-s2.0-84890462882ISBN: 978-1-4799-0356-6 (print)OAI: oai:DiVA.org:kth-122178DiVA: diva2:621216
Conference
2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013; Vancouver, BC; Canada; 26 May 2013 through 31 May 2013
Funder
EU, FP7, Seventh Framework Programme, 228024Swedish Research Council, 621-2011-5847
Note

QC 20140224

Available from: 2013-05-14 Created: 2013-05-14 Last updated: 2014-02-24Bibliographically approved

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fulltext(118 kB)111 downloads
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Wirfält, PetterJansson, Magnus

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