Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity
The strap-down inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation system are widely used for autonomous underwater vehicles (AUVs). Whereas DVL works in the water tracking mode, the velocity provided by DVL is relative to the current layer and cannot be directly u...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-08-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/16/4097 |
| _version_ | 1797583266021113856 |
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| author | Yongjiang Huang Xixiang Liu Qiantong Shao Zixuan Wang |
| author_facet | Yongjiang Huang Xixiang Liu Qiantong Shao Zixuan Wang |
| author_sort | Yongjiang Huang |
| collection | DOAJ |
| description | The strap-down inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation system are widely used for autonomous underwater vehicles (AUVs). Whereas DVL works in the water tracking mode, the velocity provided by DVL is relative to the current layer and cannot be directly used to suppress the divergence of SINS errors. Therefore, the estimation and compensation of the ocean current velocity play an essential role in improving navigation positioning accuracy. In recent works, ocean currents are considered constant over a short term in small areas. In the common KF algorithm with the ocean current as a state vector, the current velocity cannot be estimated because the current velocity and the SINS velocity error are coupled. In this paper, two virtual metrology filter (VMF) methods are proposed for estimating the velocity of ocean currents based on the properties that the currents remain unchanged at the adjacent moments. New measurement equations are constructed to decouple the current velocity and the SINS velocity error, respectively. Simulations and lake tests show that both proposed methods are effective in estimating the current velocity, and each has its advantages in estimating the ocean current velocity or the misalignment angle. |
| first_indexed | 2024-03-10T23:36:26Z |
| format | Article |
| id | doaj.art-3a037bb6e1e141dfafe80d72fc8c9bde |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T23:36:26Z |
| publishDate | 2023-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-3a037bb6e1e141dfafe80d72fc8c9bde2023-11-19T02:54:30ZengMDPI AGRemote Sensing2072-42922023-08-011516409710.3390/rs15164097Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current VelocityYongjiang Huang0Xixiang Liu1Qiantong Shao2Zixuan Wang3School of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing 210096, ChinaThe strap-down inertial navigation system (SINS) and Doppler velocity log (DVL) integrated navigation system are widely used for autonomous underwater vehicles (AUVs). Whereas DVL works in the water tracking mode, the velocity provided by DVL is relative to the current layer and cannot be directly used to suppress the divergence of SINS errors. Therefore, the estimation and compensation of the ocean current velocity play an essential role in improving navigation positioning accuracy. In recent works, ocean currents are considered constant over a short term in small areas. In the common KF algorithm with the ocean current as a state vector, the current velocity cannot be estimated because the current velocity and the SINS velocity error are coupled. In this paper, two virtual metrology filter (VMF) methods are proposed for estimating the velocity of ocean currents based on the properties that the currents remain unchanged at the adjacent moments. New measurement equations are constructed to decouple the current velocity and the SINS velocity error, respectively. Simulations and lake tests show that both proposed methods are effective in estimating the current velocity, and each has its advantages in estimating the ocean current velocity or the misalignment angle.https://www.mdpi.com/2072-4292/15/16/4097AUVSINS/DVL integrated navigation systemocean current velocityvirtual metrology filter |
| spellingShingle | Yongjiang Huang Xixiang Liu Qiantong Shao Zixuan Wang Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity Remote Sensing AUV SINS/DVL integrated navigation system ocean current velocity virtual metrology filter |
| title | Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity |
| title_full | Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity |
| title_fullStr | Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity |
| title_full_unstemmed | Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity |
| title_short | Virtual Metrology Filter-Based Algorithms for Estimating Constant Ocean Current Velocity |
| title_sort | virtual metrology filter based algorithms for estimating constant ocean current velocity |
| topic | AUV SINS/DVL integrated navigation system ocean current velocity virtual metrology filter |
| url | https://www.mdpi.com/2072-4292/15/16/4097 |
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