An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration
The emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the guarantee for the completion of various underw...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/15/5571 |
| _version_ | 1797432698823770112 |
|---|---|
| author | Chao Wang Pengyu Du Zhenduo Wang Zhongkang Wang |
| author_facet | Chao Wang Pengyu Du Zhenduo Wang Zhongkang Wang |
| author_sort | Chao Wang |
| collection | DOAJ |
| description | The emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the guarantee for the completion of various underwater tasks. Most of the current underwater positioning models do not consider the influence of the uneven underwater medium or the uncertainty of the position of the network beacon modem, which will reduce the accuracy of the positioning results. This paper proposes an underwater acoustic network positioning method based on spatial-temporal self-calibration. This method can automatically calibrate the space position of the beacon modem using only the GPS position and depth sensor information obtained in real-time. Under the asynchronous system, the influence of the inhomogeneity of the underwater medium is analyzed, and the unscented Kalman algorithm is used to estimate the position of underwater mobile nodes. Finally, the effectiveness of this method is verified by simulation and sea trials. |
| first_indexed | 2024-03-09T10:05:23Z |
| format | Article |
| id | doaj.art-514e7c7de77c483689e238851eb5e4bb |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T10:05:23Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-514e7c7de77c483689e238851eb5e4bb2023-12-01T23:09:23ZengMDPI AGSensors1424-82202022-07-012215557110.3390/s22155571An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-CalibrationChao Wang0Pengyu Du1Zhenduo Wang2Zhongkang Wang3National Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou 310000, ChinaNational Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou 310000, ChinaNational Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou 310000, ChinaNational Key Laboratory of Science and Technology on Sonar, Hangzhou Applied Acoustics Research Institute, Hangzhou 310000, ChinaThe emergence of underwater acoustic networks has greatly improved the potential capabilities of marine environment detection. In underwater acoustic network applications, node location is a basic and important task, and node location information is the guarantee for the completion of various underwater tasks. Most of the current underwater positioning models do not consider the influence of the uneven underwater medium or the uncertainty of the position of the network beacon modem, which will reduce the accuracy of the positioning results. This paper proposes an underwater acoustic network positioning method based on spatial-temporal self-calibration. This method can automatically calibrate the space position of the beacon modem using only the GPS position and depth sensor information obtained in real-time. Under the asynchronous system, the influence of the inhomogeneity of the underwater medium is analyzed, and the unscented Kalman algorithm is used to estimate the position of underwater mobile nodes. Finally, the effectiveness of this method is verified by simulation and sea trials.https://www.mdpi.com/1424-8220/22/15/5571beacon node driftspatial-temporal self-calibrationnetworked positioningunderwater acoustic networks |
| spellingShingle | Chao Wang Pengyu Du Zhenduo Wang Zhongkang Wang An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration Sensors beacon node drift spatial-temporal self-calibration networked positioning underwater acoustic networks |
| title | An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration |
| title_full | An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration |
| title_fullStr | An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration |
| title_full_unstemmed | An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration |
| title_short | An Underwater Acoustic Network Positioning Method Based on Spatial-Temporal Self-Calibration |
| title_sort | underwater acoustic network positioning method based on spatial temporal self calibration |
| topic | beacon node drift spatial-temporal self-calibration networked positioning underwater acoustic networks |
| url | https://www.mdpi.com/1424-8220/22/15/5571 |
| work_keys_str_mv | AT chaowang anunderwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT pengyudu anunderwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT zhenduowang anunderwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT zhongkangwang anunderwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT chaowang underwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT pengyudu underwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT zhenduowang underwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration AT zhongkangwang underwateracousticnetworkpositioningmethodbasedonspatialtemporalselfcalibration |