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Optimal Localization of Partially Known Signals in Unknown Noise Fields
Department of Systems and Control, Uppsala University, Uppsala, Sweden.
Dept. of Appl. El. Chalmers Univ. Tech, S-75103, Uppsala Sweden.
KTH, Superseded Departments (pre-2005), Signals, Sensors and Systems.ORCID iD: 0000-0003-2298-6774
Info. Syst. Lab., Stanfoni Univ, Stanford, CA 94905, USA.
1994 (English)In: Proc.  IEEE International Conference on Acoustics, Speech, and Signal Processing ICASSP-94, IEEE , 1994, p. 217-220Conference paper, Published paper (Refereed)
Abstract [en]

Most methods for sensor array signal processing require the covariance matrix of the background noise to beknown. Various techniques for overcoming this limitation have recently been proposed. While most of these are based on assumptions on the noise, we present herein an alternative approach based on partial knowledge of thesignals. Methods yielding minimum variance estimates for the model in question are presented and analyzed.

Place, publisher, year, edition, pages
IEEE , 1994. p. 217-220
Keywords [en]
Background noise, Colored noise, Contracts, Covariance matrix, Direction of arrival estimation, Phased arrays, Sensor arrays, Sensor phenomena and characterization, Signal processing, Yield estimation
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-92598DOI: 10.1109/ICASSP.1994.389835Scopus ID: 2-s2.0-4243657363OAI: oai:DiVA.org:kth-92598DiVA, id: diva2:513872
Conference
IEEE International Conference on Acoustics, Speech, and Signal Processing, 1994. ICASSP-94. 19-22 Apr 1994, Adelaide, SA
Note
NR 20140805Available from: 2012-04-03 Created: 2012-04-03 Last updated: 2022-06-24Bibliographically approved

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Ottersten, Björn

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