Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array
Beamspace processing has become much attractive in recent radar and wireless communication applications, since the advantages of complexity reduction and of performance improvements in array signal processing. In this paper, we concentrate on the beamspace DOA estimation of linear array via atomic n...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/8/2222 |
| _version_ | 1827718663254310912 |
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| author | Jie Pan Fu Jiang |
| author_facet | Jie Pan Fu Jiang |
| author_sort | Jie Pan |
| collection | DOAJ |
| description | Beamspace processing has become much attractive in recent radar and wireless communication applications, since the advantages of complexity reduction and of performance improvements in array signal processing. In this paper, we concentrate on the beamspace DOA estimation of linear array via atomic norm minimization (ANM). The existed generalized linear spectrum estimation based ANM approaches suffer from the high computational complexity for large scale array, since their complexity depends upon the number of sensors. To deal with this problem, we develop a low dimensional semidefinite programming (SDP) implementation of beamspace atomic norm minimization (BS-ANM) approach for DFT beamspace based on the super resolution theory on the semi-algebraic set. Then, a computational efficient iteration algorithm is proposed based on alternating direction method of multipliers (ADMM) approach. We develop the covariance based DOA estimation methods via BS-ANM and apply the BS-ANM based DOA estimation method to the channel estimation problem for massive MIMO systems. Simulation results demonstrate that the proposed methods exhibit the superior performance compared to the state-of-the-art counterparts. |
| first_indexed | 2024-03-10T20:28:36Z |
| format | Article |
| id | doaj.art-f06bb3bf7ff94450be8466170c79c890 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T20:28:36Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-f06bb3bf7ff94450be8466170c79c8902023-11-19T21:38:42ZengMDPI AGSensors1424-82202020-04-01208222210.3390/s20082222Low Complexity Beamspace Super Resolution for DOA Estimation of Linear ArrayJie Pan0Fu Jiang1College of Information Engineering, Yangzhou University, Yangzhou 225009, ChinaCollege of Information Engineering, Yangzhou University, Yangzhou 225009, ChinaBeamspace processing has become much attractive in recent radar and wireless communication applications, since the advantages of complexity reduction and of performance improvements in array signal processing. In this paper, we concentrate on the beamspace DOA estimation of linear array via atomic norm minimization (ANM). The existed generalized linear spectrum estimation based ANM approaches suffer from the high computational complexity for large scale array, since their complexity depends upon the number of sensors. To deal with this problem, we develop a low dimensional semidefinite programming (SDP) implementation of beamspace atomic norm minimization (BS-ANM) approach for DFT beamspace based on the super resolution theory on the semi-algebraic set. Then, a computational efficient iteration algorithm is proposed based on alternating direction method of multipliers (ADMM) approach. We develop the covariance based DOA estimation methods via BS-ANM and apply the BS-ANM based DOA estimation method to the channel estimation problem for massive MIMO systems. Simulation results demonstrate that the proposed methods exhibit the superior performance compared to the state-of-the-art counterparts.https://www.mdpi.com/1424-8220/20/8/2222DOA estimationatomic norm minimizationsemidefinite programmingbeamspace |
| spellingShingle | Jie Pan Fu Jiang Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array Sensors DOA estimation atomic norm minimization semidefinite programming beamspace |
| title | Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array |
| title_full | Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array |
| title_fullStr | Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array |
| title_full_unstemmed | Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array |
| title_short | Low Complexity Beamspace Super Resolution for DOA Estimation of Linear Array |
| title_sort | low complexity beamspace super resolution for doa estimation of linear array |
| topic | DOA estimation atomic norm minimization semidefinite programming beamspace |
| url | https://www.mdpi.com/1424-8220/20/8/2222 |
| work_keys_str_mv | AT jiepan lowcomplexitybeamspacesuperresolutionfordoaestimationoflineararray AT fujiang lowcomplexitybeamspacesuperresolutionfordoaestimationoflineararray |