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Analysis of Subspace Fitting based Methods for Sensor Array Processing
Stanford University, CA, USA.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology. Stanford University, CA, USA.
1989 (English)Report (Other academic)
Abstract [en]

The problem of estimating signal parameters from sensor array measurements is addressed. A general multidimensional signal subspace method, called the weighted subspace fitting (WSF) method, is proposed. The relationship of WSF to other signal subspace methods as well as the relation to the deterministic maximum-likelihood (ML) method is discussed. The asymptotic properties of WSF are presented for a general weighting. This result includes the properties of ML as a special case. The weighting that minimizes the estimation error covariance is given, resulting in a method that always outperforms ML. A numerical example is presented, demonstrating that the optimally weighted WSF method can give notably lower variance for highly correlated signals. Simulations are included to substantiate the analysis.

Place, publisher, year, edition, pages
Linköping: Linköping University , 1989. , 5 p.
LiTH-ISY-I, ISSN 8765-4321 ; 985
Keyword [en]
Parameter estimation, Signal processing, Subspace fitting, Sensor array processing
National Category
Control Engineering
URN: urn:nbn:se:liu:diva-104085OAI: diva2:694532
Available from: 2014-02-06 Created: 2014-02-06 Last updated: 2014-02-06

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ReferencesLink to record
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