Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC
The problem of poor real-time capability, a large number of traversals and the long operation time of the MUSIC algorithm bring great difficulties to the application of DOA estimation. For the above problems, this paper fuses MUSIC algorithm and genetic algorithm and proposes an improved genetic MUS...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10172162/ |
| _version_ | 1827901041246470144 |
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| author | Chaofeng Lan Huan Chen Lei Zhang Rui Guo Chuang Han Dajun Luo |
| author_facet | Chaofeng Lan Huan Chen Lei Zhang Rui Guo Chuang Han Dajun Luo |
| author_sort | Chaofeng Lan |
| collection | DOAJ |
| description | The problem of poor real-time capability, a large number of traversals and the long operation time of the MUSIC algorithm bring great difficulties to the application of DOA estimation. For the above problems, this paper fuses MUSIC algorithm and genetic algorithm and proposes an improved genetic MUSIC algorithm (GA-MUSIC). Also, improvement strategies are proposed for the three operators of selection, crossover, and variation of the genetic algorithm. The GA-MUSIC was simulated for DOA estimation to verify the effectiveness of this algorithm. The research shows that the GA-MUSIC proposed in this paper has the best operational performance at different precisions and SNRs. This algorithm can effectively reduce the iterative computation of the algorithm with better real-time performance, and the search success rate is above 95% while ensuring accuracy. Furthermore, this paper corroborates that the proposed improved genetic MUSIC algorithm can achieve better performance in single signals and incoherent multi-signal sources. It can be seen that the algorithm in this paper can effectively solve the problems of low success rates of DOA estimation searches and poor real-time performance and has a significant reference value for practical engineering applications. |
| first_indexed | 2024-03-12T23:40:05Z |
| format | Article |
| id | doaj.art-c9aeb136bfc24483ad3f12f2836b2a1d |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-12T23:40:05Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-c9aeb136bfc24483ad3f12f2836b2a1d2023-07-14T23:00:23ZengIEEEIEEE Access2169-35362023-01-0111694746948510.1109/ACCESS.2023.329221810172162Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSICChaofeng Lan0https://orcid.org/0000-0003-4667-0635Huan Chen1Lei Zhang2https://orcid.org/0000-0002-3594-0778Rui Guo3https://orcid.org/0000-0002-1872-6139Chuang Han4Dajun Luo5School of Measurement and Communication Engineering, Harbin University of Science and Technology, Harbin, ChinaChina Ship Development and Design Center, Wuhan, ChinaBeidahuang Industry Group General Hospital, Harbin, ChinaSchool of Measurement and Communication Engineering, Harbin University of Science and Technology, Harbin, ChinaSchool of Measurement and Communication Engineering, Harbin University of Science and Technology, Harbin, ChinaSchool of Measurement and Communication Engineering, Harbin University of Science and Technology, Harbin, ChinaThe problem of poor real-time capability, a large number of traversals and the long operation time of the MUSIC algorithm bring great difficulties to the application of DOA estimation. For the above problems, this paper fuses MUSIC algorithm and genetic algorithm and proposes an improved genetic MUSIC algorithm (GA-MUSIC). Also, improvement strategies are proposed for the three operators of selection, crossover, and variation of the genetic algorithm. The GA-MUSIC was simulated for DOA estimation to verify the effectiveness of this algorithm. The research shows that the GA-MUSIC proposed in this paper has the best operational performance at different precisions and SNRs. This algorithm can effectively reduce the iterative computation of the algorithm with better real-time performance, and the search success rate is above 95% while ensuring accuracy. Furthermore, this paper corroborates that the proposed improved genetic MUSIC algorithm can achieve better performance in single signals and incoherent multi-signal sources. It can be seen that the algorithm in this paper can effectively solve the problems of low success rates of DOA estimation searches and poor real-time performance and has a significant reference value for practical engineering applications.https://ieeexplore.ieee.org/document/10172162/DOA estimationMUSIC algorithmgenetic algorithmGA-MUSICreal-time |
| spellingShingle | Chaofeng Lan Huan Chen Lei Zhang Rui Guo Chuang Han Dajun Luo Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC IEEE Access DOA estimation MUSIC algorithm genetic algorithm GA-MUSIC real-time |
| title | Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC |
| title_full | Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC |
| title_fullStr | Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC |
| title_full_unstemmed | Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC |
| title_short | Underwater Acoustic DOA Estimation of Incoherent Signal Based on Improved GA-MUSIC |
| title_sort | underwater acoustic doa estimation of incoherent signal based on improved ga music |
| topic | DOA estimation MUSIC algorithm genetic algorithm GA-MUSIC real-time |
| url | https://ieeexplore.ieee.org/document/10172162/ |
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