Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise
Recently, many direction-of-arrival (DOA) estimation techniques based on sparse representation have been proposed. However, these techniques often suffer from performance degradation issues in the presence of impulsive noise. This paper aims to overcome this challenge in conventional sparse-based te...
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MDPI AG
2023-09-01
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| Series: | Journal of Marine Science and Engineering |
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| Online Access: | https://www.mdpi.com/2077-1312/11/9/1798 |
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| author | Zhiqiang Liu Yongqing Zhang Weidong Wang Xiangshui Li Hui Li Wentao Shi Wasiq Ali |
| author_facet | Zhiqiang Liu Yongqing Zhang Weidong Wang Xiangshui Li Hui Li Wentao Shi Wasiq Ali |
| author_sort | Zhiqiang Liu |
| collection | DOAJ |
| description | Recently, many direction-of-arrival (DOA) estimation techniques based on sparse representation have been proposed. However, these techniques often suffer from performance degradation issues in the presence of impulsive noise. This paper aims to overcome this challenge in conventional sparse-based techniques on an acoustic vector sensor array (AVSA). Firstly, to remove high outliers from the array output data, the output information of the AVSA is weighted by using the infinite norm. To further suppress outliers, a <i>p</i>-order cost function is formulated by extending the Frobenius norm to lower order, and then the expression of the signal power is quantified. Lastly, the DOA is approximated on the signal power by a spectral peak search mechanism. DOA estimation results based on Monte Carlo simulations validate the accuracy and robustness of the proposed techniques herein compared to the current, available methods in the context of intense impulsive noise, low generalized signal–to–noise ratio (GSNR), and a smaller number of snapshots. |
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| issn | 2077-1312 |
| language | English |
| last_indexed | 2024-03-10T22:34:57Z |
| publishDate | 2023-09-01 |
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| spelling | doaj.art-31b4a57794e44ba2bee4b8700db7c7472023-11-19T11:27:31ZengMDPI AGJournal of Marine Science and Engineering2077-13122023-09-01119179810.3390/jmse11091798Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive NoiseZhiqiang Liu0Yongqing Zhang1Weidong Wang2Xiangshui Li3Hui Li4Wentao Shi5Wasiq Ali6School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454003, ChinaSchool of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaSchool of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaSchool of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaSchool of Physics and Electronic Information Engineering, Henan Polytechnic University, Jiaozuo 454003, ChinaOcean Institute, Northwestern Polytechnical University, Taicang 215400, ChinaCollege of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, ChinaRecently, many direction-of-arrival (DOA) estimation techniques based on sparse representation have been proposed. However, these techniques often suffer from performance degradation issues in the presence of impulsive noise. This paper aims to overcome this challenge in conventional sparse-based techniques on an acoustic vector sensor array (AVSA). Firstly, to remove high outliers from the array output data, the output information of the AVSA is weighted by using the infinite norm. To further suppress outliers, a <i>p</i>-order cost function is formulated by extending the Frobenius norm to lower order, and then the expression of the signal power is quantified. Lastly, the DOA is approximated on the signal power by a spectral peak search mechanism. DOA estimation results based on Monte Carlo simulations validate the accuracy and robustness of the proposed techniques herein compared to the current, available methods in the context of intense impulsive noise, low generalized signal–to–noise ratio (GSNR), and a smaller number of snapshots.https://www.mdpi.com/2077-1312/11/9/1798direction-of-arrival (DOA) estimationacoustic vector sensor array (AVSA)low-order processingimpulsive noise |
| spellingShingle | Zhiqiang Liu Yongqing Zhang Weidong Wang Xiangshui Li Hui Li Wentao Shi Wasiq Ali Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise Journal of Marine Science and Engineering direction-of-arrival (DOA) estimation acoustic vector sensor array (AVSA) low-order processing impulsive noise |
| title | Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise |
| title_full | Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise |
| title_fullStr | Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise |
| title_full_unstemmed | Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise |
| title_short | Infinite Weighted <i>p</i>-Norm Sparse Iterative DOA Estimation via Acoustic Vector Sensor Array under Impulsive Noise |
| title_sort | infinite weighted i p i norm sparse iterative doa estimation via acoustic vector sensor array under impulsive noise |
| topic | direction-of-arrival (DOA) estimation acoustic vector sensor array (AVSA) low-order processing impulsive noise |
| url | https://www.mdpi.com/2077-1312/11/9/1798 |
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