A discretization-free sparse and parametric approach for linear array signal processing
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 compu...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2014
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| Online Access: | https://hdl.handle.net/10356/103459 http://hdl.handle.net/10220/24496 |
| _version_ | 1811682473671655424 |
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| author | Zhang, Cishen Yang, Zai Xie, Lihua |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Zhang, Cishen Yang, Zai Xie, Lihua |
| author_sort | Zhang, Cishen |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T03:57:24Z |
| format | Journal Article |
| id | ntu-10356/103459 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:57:24Z |
| publishDate | 2014 |
| record_format | dspace |
| spelling | ntu-10356/1034592020-03-07T14:00:36Z A discretization-free sparse and parametric approach for linear array signal processing Zhang, Cishen Yang, Zai Xie, Lihua School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing 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. Accepted version 2014-12-19T08:05:00Z 2019-12-06T21:13:09Z 2014-12-19T08:05:00Z 2019-12-06T21:13:09Z 2014 2014 Journal Article 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. 1053-587X https://hdl.handle.net/10356/103459 http://hdl.handle.net/10220/24496 10.1109/TSP.2014.2339792 en IEEE transactions on signal processing © 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]. 15 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Zhang, Cishen Yang, Zai Xie, Lihua A discretization-free sparse and parametric approach for linear array signal processing |
| title | A discretization-free sparse and parametric approach for linear array signal processing |
| title_full | A discretization-free sparse and parametric approach for linear array signal processing |
| title_fullStr | A discretization-free sparse and parametric approach for linear array signal processing |
| title_full_unstemmed | A discretization-free sparse and parametric approach for linear array signal processing |
| title_short | A discretization-free sparse and parametric approach for linear array signal processing |
| title_sort | discretization free sparse and parametric approach for linear array signal processing |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing |
| url | https://hdl.handle.net/10356/103459 http://hdl.handle.net/10220/24496 |
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