A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources
In this paper, we investigate a covariance matrix reconstruction approach (CMRA) for direction-of-arrival (DOA) estimation in correlated/coherent sources scenario. We incorporate a spatial filtering (SF) model into our recently developed method CMRA in order to enhance its adaptation ability. In par...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8476564/ |
| _version_ | 1831646037796716544 |
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| author | Xiaohuan Wu Wei-Ping Zhu Jun Yan Zeyun Zhang |
| author_facet | Xiaohuan Wu Wei-Ping Zhu Jun Yan Zeyun Zhang |
| author_sort | Xiaohuan Wu |
| collection | DOAJ |
| description | In this paper, we investigate a covariance matrix reconstruction approach (CMRA) for direction-of-arrival (DOA) estimation in correlated/coherent sources scenario. We incorporate a spatial filtering (SF) model into our recently developed method CMRA in order to enhance its adaptation ability. In particular, a sliding window scheme is proposed to estimate the number of sources, and an iterative procedure is provided to estimate the DOAs of the signals. Since the original CMRA provides inaccurate estimate of the noise power which is undesirable during iterations, a new update rule for the noise power is proposed. Moreover, we derive a fast implementation of the SF-CMRA to accelerate the DOA estimation in each iteration. The proposed methods are suitable for both uniform and sparse linear arrays and are able to provide accurate estimates of DOAs, signal powers, and noise power. We also show that the proposed algorithmic framework can be easily extended to other gridless DOA estimation methods for accuracy improvement. Simulation results are provided to illustrate the superiority of our proposed methods. |
| first_indexed | 2024-12-19T13:47:26Z |
| format | Article |
| id | doaj.art-6758458d99c2409e9408babed89033cd |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T13:47:26Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-6758458d99c2409e9408babed89033cd2022-12-21T20:18:49ZengIEEEIEEE Access2169-35362018-01-016564025641010.1109/ACCESS.2018.28725788476564A Spatial Filtering Based Gridless DOA Estimation Method for Coherent SourcesXiaohuan Wu0https://orcid.org/0000-0003-3190-6115Wei-Ping Zhu1https://orcid.org/0000-0001-7955-7044Jun Yan2https://orcid.org/0000-0001-7113-0249Zeyun Zhang3Key Lab of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, ChinaDepartment of Electrical and Computer Engineering, Concordia University, Montreal, CanadaKey Lab of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, ChinaKey Lab of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, ChinaIn this paper, we investigate a covariance matrix reconstruction approach (CMRA) for direction-of-arrival (DOA) estimation in correlated/coherent sources scenario. We incorporate a spatial filtering (SF) model into our recently developed method CMRA in order to enhance its adaptation ability. In particular, a sliding window scheme is proposed to estimate the number of sources, and an iterative procedure is provided to estimate the DOAs of the signals. Since the original CMRA provides inaccurate estimate of the noise power which is undesirable during iterations, a new update rule for the noise power is proposed. Moreover, we derive a fast implementation of the SF-CMRA to accelerate the DOA estimation in each iteration. The proposed methods are suitable for both uniform and sparse linear arrays and are able to provide accurate estimates of DOAs, signal powers, and noise power. We also show that the proposed algorithmic framework can be easily extended to other gridless DOA estimation methods for accuracy improvement. Simulation results are provided to illustrate the superiority of our proposed methods.https://ieeexplore.ieee.org/document/8476564/DOA estimationgridless methodsToeplitz structurecoherent sources |
| spellingShingle | Xiaohuan Wu Wei-Ping Zhu Jun Yan Zeyun Zhang A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources IEEE Access DOA estimation gridless methods Toeplitz structure coherent sources |
| title | A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources |
| title_full | A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources |
| title_fullStr | A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources |
| title_full_unstemmed | A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources |
| title_short | A Spatial Filtering Based Gridless DOA Estimation Method for Coherent Sources |
| title_sort | spatial filtering based gridless doa estimation method for coherent sources |
| topic | DOA estimation gridless methods Toeplitz structure coherent sources |
| url | https://ieeexplore.ieee.org/document/8476564/ |
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