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Array Processing in Correlated Noise Fields Using Instrumental Variables and Subspace Fitting
Information Systems Lab, Stanford University, Stanford, CA 94305, USA.
School of Electrical Engineering, Uppsala University, Uppsala, Sweden.
KTH, School of Electrical Engineering (EES).ORCID iD: 0000-0003-2298-6774
1992 (English)In: The Twenty-Sixth Asilomar Conference on Signals, Systems and Computers, IEEE , 1992, 1147-1151 p.Conference paper (Refereed)
Abstract [en]

An improved technique for direction-of-arrival estimation of temporally correlated signals in the presence of spatially colored, but temporally uncorrelated, noise is presented. The method is particularly suited to applications in which the receiver bandwidth exceeds that of the emitter signals. A statistical performance analysis shows that the method nearly achieves the deterministic Cramer-Rao bound if the signals are sufficiently predictable. A Monte Carlo experiment suggests that the theoretical estimation error variance well predicts the empirical mean square error down to the threshold region.

Place, publisher, year, edition, pages
IEEE , 1992. 1147-1151 p.
Keyword [en]
Additive noise, Array signal processing, Background noise, Colored noise, Covariance matrix, Data engineering, Information systems, Instruments, Knowledge engineering, Sensor arrays
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-92635DOI: 10.1109/ACSSC.1992.269119OAI: diva2:514156
The Twenty-Sixth Asilomar Conference on Signals, Systems and Computers, 26-28 Oct 1992, Pacific Grove, CA
NR 20140805Available from: 2012-04-05 Created: 2012-04-05 Last updated: 2012-04-05Bibliographically approved

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Ottersten, Björn
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School of Electrical Engineering (EES)
Signal Processing

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ReferencesLink to record
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