A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation
Direction of arrival (DOA) estimation using a uniform linear array (ULA) is a classical problem in array signal processing. In this paper, we focus on DOA estimation based on the maximum likelihood (ML) criterion, transform the estimation problem into a novel formulation, named as sum-of-squares (SO...
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| Format: | Article |
| Language: | English |
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MDPI AG
2016-12-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/16/12/2191 |
| _version_ | 1811299527993327616 |
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| author | Shu Cai Quan Zhou Hongbo Zhu |
| author_facet | Shu Cai Quan Zhou Hongbo Zhu |
| author_sort | Shu Cai |
| collection | DOAJ |
| description | Direction of arrival (DOA) estimation using a uniform linear array (ULA) is a classical problem in array signal processing. In this paper, we focus on DOA estimation based on the maximum likelihood (ML) criterion, transform the estimation problem into a novel formulation, named as sum-of-squares (SOS), and then solve it using semidefinite programming (SDP). We first derive the SOS and SDP method for DOA estimation in the scenario of a single source and then extend it under the framework of alternating projection for multiple DOA estimation. The simulations demonstrate that the SOS- and SDP-based algorithms can provide stable and accurate DOA estimation when the number of snapshots is small and the signal-to-noise ratio (SNR) is low. Moveover, it has a higher spatial resolution compared to existing methods based on the ML criterion. |
| first_indexed | 2024-04-13T06:37:08Z |
| format | Article |
| id | doaj.art-189b709c862142c5b65d83e6e9a58196 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T06:37:08Z |
| publishDate | 2016-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-189b709c862142c5b65d83e6e9a581962022-12-22T02:57:51ZengMDPI AGSensors1424-82202016-12-011612219110.3390/s16122191s16122191A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA EstimationShu Cai0Quan Zhou1Hongbo Zhu2Jiangsu Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaKey Laboratory of Ministry of Education for Broad Band Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaJiangsu Key Laboratory of Wireless Communication, Nanjing University of Posts and Telecommunications, Nanjing 210003, ChinaDirection of arrival (DOA) estimation using a uniform linear array (ULA) is a classical problem in array signal processing. In this paper, we focus on DOA estimation based on the maximum likelihood (ML) criterion, transform the estimation problem into a novel formulation, named as sum-of-squares (SOS), and then solve it using semidefinite programming (SDP). We first derive the SOS and SDP method for DOA estimation in the scenario of a single source and then extend it under the framework of alternating projection for multiple DOA estimation. The simulations demonstrate that the SOS- and SDP-based algorithms can provide stable and accurate DOA estimation when the number of snapshots is small and the signal-to-noise ratio (SNR) is low. Moveover, it has a higher spatial resolution compared to existing methods based on the ML criterion.http://www.mdpi.com/1424-8220/16/12/2191DOA estimationmaximum likelihooduniform linear arraysum-of-squaressemidefinite programmingalternating projection |
| spellingShingle | Shu Cai Quan Zhou Hongbo Zhu A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation Sensors DOA estimation maximum likelihood uniform linear array sum-of-squares semidefinite programming alternating projection |
| title | A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation |
| title_full | A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation |
| title_fullStr | A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation |
| title_full_unstemmed | A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation |
| title_short | A Sum-of-Squares and Semidefinite Programming Approach for Maximum Likelihood DOA Estimation |
| title_sort | sum of squares and semidefinite programming approach for maximum likelihood doa estimation |
| topic | DOA estimation maximum likelihood uniform linear array sum-of-squares semidefinite programming alternating projection |
| url | http://www.mdpi.com/1424-8220/16/12/2191 |
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