An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering
The ultra-short baseline underwater positioning is one of the most widely applied methods in underwater positioning and navigation due to its simplicity, efficiency, low cost, and accuracy. However, there exists environmental noise, which has negative impacts on the positioning accuracy during the u...
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| Format: | Article |
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MDPI AG
2020-12-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/1/143 |
| _version_ | 1797543315969671168 |
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| author | Qinghua Luo Xiaozhen Yan Chunyu Ju Yunsai Chen Zhenhua Luo |
| author_facet | Qinghua Luo Xiaozhen Yan Chunyu Ju Yunsai Chen Zhenhua Luo |
| author_sort | Qinghua Luo |
| collection | DOAJ |
| description | The ultra-short baseline underwater positioning is one of the most widely applied methods in underwater positioning and navigation due to its simplicity, efficiency, low cost, and accuracy. However, there exists environmental noise, which has negative impacts on the positioning accuracy during the ultra-short baseline (USBL) positioning process, which results in a large positioning error. The positioning result may lead to wrong decision-making in the latter processing. So, it is necessary to consider the error sources, and take effective measurements to minimize the negative impact of the noise. In our work, we propose a USBL positioning system with Kalman filtering to improve the positioning accuracy. In this system, we first explore a new kind of element array to accurately capture the acoustic signals from the object. We then organically combine the Kalman filters with the array elements to filter the acoustic signals, using the minimum mean-square error rule to obtain accurate acoustic signals. We got the high-precision phase difference information based on the non-equidistant quaternary original array and the phase difference acquisition mechanism. Finally, on account of the obtained accurate phase difference information and position calculation, we determined the coordinates of the underwater target. Comprehensive evaluation results demonstrate that our proposed USBL positioning method based on the Kalman filter algorithm can effectively enhance the positioning accuracy. |
| first_indexed | 2024-03-10T13:43:46Z |
| format | Article |
| id | doaj.art-a64dff58a03e4c709e1f6738cc3c96e4 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T13:43:46Z |
| publishDate | 2020-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-a64dff58a03e4c709e1f6738cc3c96e42023-11-21T02:50:13ZengMDPI AGSensors1424-82202020-12-0121114310.3390/s21010143An Ultra-Short Baseline Underwater Positioning System with Kalman FilteringQinghua Luo0Xiaozhen Yan1Chunyu Ju2Yunsai Chen3Zhenhua Luo4School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaSchool of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaSchool of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, ChinaChina National Deep Sea Center, Qingdao 266237, ChinaSchool of Water Energy and Environment, Cranfield University, Cranfield MK43 0AL, UKThe ultra-short baseline underwater positioning is one of the most widely applied methods in underwater positioning and navigation due to its simplicity, efficiency, low cost, and accuracy. However, there exists environmental noise, which has negative impacts on the positioning accuracy during the ultra-short baseline (USBL) positioning process, which results in a large positioning error. The positioning result may lead to wrong decision-making in the latter processing. So, it is necessary to consider the error sources, and take effective measurements to minimize the negative impact of the noise. In our work, we propose a USBL positioning system with Kalman filtering to improve the positioning accuracy. In this system, we first explore a new kind of element array to accurately capture the acoustic signals from the object. We then organically combine the Kalman filters with the array elements to filter the acoustic signals, using the minimum mean-square error rule to obtain accurate acoustic signals. We got the high-precision phase difference information based on the non-equidistant quaternary original array and the phase difference acquisition mechanism. Finally, on account of the obtained accurate phase difference information and position calculation, we determined the coordinates of the underwater target. Comprehensive evaluation results demonstrate that our proposed USBL positioning method based on the Kalman filter algorithm can effectively enhance the positioning accuracy.https://www.mdpi.com/1424-8220/21/1/143acoustic signal detectionadaptive filtersKalman filterssignal denoising |
| spellingShingle | Qinghua Luo Xiaozhen Yan Chunyu Ju Yunsai Chen Zhenhua Luo An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering Sensors acoustic signal detection adaptive filters Kalman filters signal denoising |
| title | An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering |
| title_full | An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering |
| title_fullStr | An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering |
| title_full_unstemmed | An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering |
| title_short | An Ultra-Short Baseline Underwater Positioning System with Kalman Filtering |
| title_sort | ultra short baseline underwater positioning system with kalman filtering |
| topic | acoustic signal detection adaptive filters Kalman filters signal denoising |
| url | https://www.mdpi.com/1424-8220/21/1/143 |
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