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Instrumental Variable Approach to Array Processing in Spatially Correlated Noise Fields
Polytechnic Institute of Bucharest, Romania.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
1994 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 42, no 1, 121-133 p.Article in journal (Refereed) Published
Abstract [en]

High-performance signal parameter estimation from sensor array data is a problem which has received much attention. A number of so-called eigenvector (EV) techniques such as MUSIC, ESPRIT, WSF, and MODE have been proposed in the literature. The EV techniques for array processing require knowledge of the spatial noise correlation matrix that constitutes a significant drawback. A novel instrumental variable (IV) approach to the sensor array problem is proposed. The IV technique relies on the same basic geometric properties as the EV methods to obtain parameter estimates. However, by exploiting the temporal correlation of the source signals, no knowledge of the spatial noise covariance is required. The asymptotic properties of the IV estimator are examined and an optimal IV method is derived. Computer simulations are presented to study the properties of the IV estimators in samples of practical length. The proposed algorithm is also shown to perform better than MUSIC on a full-scale passive sonar experiment.

Place, publisher, year, edition, pages
1994. Vol. 42, no 1, 121-133 p.
Keyword [en]
Acoustic signal processing, Array signal processing, Correlation theory, Eigenvalues, Noise, Parameter estimation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56335DOI: 10.1109/78.258127OAI: oai:DiVA.org:liu-56335DiVA: diva2:318622
Available from: 2010-05-09 Created: 2010-05-07 Last updated: 2017-12-12

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