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SPICE: A Sparse Covariance-Based Estimation Method for Array Processing
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2011 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 59, no 2, 629-638 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a novel SParse Iterative Covariance-based Estimation approach, abbreviated as SPICE, to array processing. The proposed approach is obtained by the minimization of a covariance matrix fitting criterion and is particularly useful in many-snapshot cases but can be used even in single-snapshot situations. SPICE has several unique features not shared by other sparse estimation methods: it has a simple and sound statistical foundation, it takes account of the noise in the data in a natural manner, it does not require the user to make any difficult selection of hyperparameters, and yet it has global convergence properties.

Place, publisher, year, edition, pages
2011. Vol. 59, no 2, 629-638 p.
Keyword [en]
Array processing, covariance fitting, direction-of-arrival (DOA) estimation, sparse parameter estimation
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:uu:diva-148954DOI: 10.1109/TSP.2010.2090525ISI: 000286111100014OAI: oai:DiVA.org:uu-148954DiVA: diva2:403568
Available from: 2011-03-14 Created: 2011-03-14 Last updated: 2017-12-11Bibliographically approved

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Stoica, PeterBabu, Prabhu

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