Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/103459
Title: A discretization-free sparse and parametric approach for linear array signal processing
Authors: Zhang, Cishen
Yang, Zai
Xie, Lihua
Keywords: DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Issue Date: 2014
Source: Yang, Z., Xie, L., & Zhang, C. (2014). A discretization-free sparse and parametric approach for linear array signal processing. IEEE transactions on signal processing, 62(19), 4959-4973.
Series/Report no.: IEEE transactions on signal processing
Abstract: Direction of arrival (DOA) estimation in array processing using uniform/sparse linear arrays is concerned in this paper. While sparse methods via approximate parameter discretization have been popular in the past decade, the discretization may cause problems, e.g., modeling error and increased computations due to dense sampling. In this paper, an exact discretization-free method, named as sparse and parametric approach (SPA), is proposed for uniform and sparse linear arrays. SPA carries out parameter estimation in the continuous range based on well-established covariance fitting criteria and convex optimization. It guarantees to produce a sparse parameter estimate without discretization required by existing sparse methods. Theoretical analysis shows that the SPA parameter estimator is a large-snapshot realization of the maximum likelihood estimator and is statistically consistent (in the number of snapshots) under uncorrelated sources. Other merits of SPA include improved resolution, applicability to arbitrary number of snapshots, robustness to correlation of the sources and no requirement of user-parameters. Numerical simulations are carried out to verify our analysis and demonstrate advantages of SPA compared to existing methods.
URI: https://hdl.handle.net/10356/103459
http://hdl.handle.net/10220/24496
ISSN: 1053-587X
DOI: http://dx.doi.org/10.1109/TSP.2014.2339792
Rights: © 2014 IEEE. This is the author created version of a work that has been peer reviewed and accepted for publication by IEEE Transactions on Signal Processing, IEEE. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [http://dx.doi.org/10.1109/TSP.2014.2339792].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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