SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation
Motivated by the problem that water-track Doppler Velocity Log (DVL) cannot effectively suppress the error accumulation of strap-down inertial navigation system (SINS), this paper proposes a novel SINS/DVL integrated navigation algorithm for deep and long cruising range Human Occupied Vehicle (HOV)....
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doaj-12c2fb4090a048d6b47ad6ead0695f622021-04-07T23:00:50ZengIEEEIEEE Access2169-35362021-01-019513325134210.1109/ACCESS.2021.30694699389537SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater NavigationXianjun Liu0https://orcid.org/0000-0003-3301-9771Xixiang Liu1https://orcid.org/0000-0001-6847-1405Lei Wang2Yongjiang Huang3Zixuan Wang4School of Instrument Science and Engineering, Southeast University, Nanjing, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing, ChinaCollege of Optical Science and Engineering, Zhejiang University, Hangzhou, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing, ChinaSchool of Instrument Science and Engineering, Southeast University, Nanjing, ChinaMotivated by the problem that water-track Doppler Velocity Log (DVL) cannot effectively suppress the error accumulation of strap-down inertial navigation system (SINS), this paper proposes a novel SINS/DVL integrated navigation algorithm for deep and long cruising range Human Occupied Vehicle (HOV). Such algorithm decomposes the navigation process into two tightly coupled working modes: alignment mode and navigation mode. In the alignment mode, HOV is controlled to perform horizontal circular motion for several minutes to realize Self-Aided SINS. Combining the precise navigation solutions provided by Self-Aided SINS and measurements from DVL with water track, recursive least square (RLS) algorithm is adopted to estimate heading misalignment angle between SINS and DVL and horizontal ocean current velocity. In the navigation mode, both horizontal ocean current velocity obtained in the alignment mode and DVL measurements are utilized to assist SINS, thus enabling SINS/DVL/Current integrated navigation. A square trajectory with a navigation-grade inertial measurement unit (IMU) is simulated to evaluate the proposed SINS/DVL integrated navigation algorithm. Simulation results show that the proposed SINS/DVL integrated navigation is capable of suppressing SINS error divergence effectively and efficiently. In addition, the feasibility and effectiveness of Self-Aided SINS based on horizontal circular motion is also verified by field test with real IMU data.https://ieeexplore.ieee.org/document/9389537/HOVSINSDVLmidwater navigationself-aided SINS |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xianjun Liu Xixiang Liu Lei Wang Yongjiang Huang Zixuan Wang |
spellingShingle |
Xianjun Liu Xixiang Liu Lei Wang Yongjiang Huang Zixuan Wang SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation IEEE Access HOV SINS DVL midwater navigation self-aided SINS |
author_facet |
Xianjun Liu Xixiang Liu Lei Wang Yongjiang Huang Zixuan Wang |
author_sort |
Xianjun Liu |
title |
SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation |
title_short |
SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation |
title_full |
SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation |
title_fullStr |
SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation |
title_full_unstemmed |
SINS/DVL Integrated System With Current and Misalignment Estimation for Midwater Navigation |
title_sort |
sins/dvl integrated system with current and misalignment estimation for midwater navigation |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Motivated by the problem that water-track Doppler Velocity Log (DVL) cannot effectively suppress the error accumulation of strap-down inertial navigation system (SINS), this paper proposes a novel SINS/DVL integrated navigation algorithm for deep and long cruising range Human Occupied Vehicle (HOV). Such algorithm decomposes the navigation process into two tightly coupled working modes: alignment mode and navigation mode. In the alignment mode, HOV is controlled to perform horizontal circular motion for several minutes to realize Self-Aided SINS. Combining the precise navigation solutions provided by Self-Aided SINS and measurements from DVL with water track, recursive least square (RLS) algorithm is adopted to estimate heading misalignment angle between SINS and DVL and horizontal ocean current velocity. In the navigation mode, both horizontal ocean current velocity obtained in the alignment mode and DVL measurements are utilized to assist SINS, thus enabling SINS/DVL/Current integrated navigation. A square trajectory with a navigation-grade inertial measurement unit (IMU) is simulated to evaluate the proposed SINS/DVL integrated navigation algorithm. Simulation results show that the proposed SINS/DVL integrated navigation is capable of suppressing SINS error divergence effectively and efficiently. In addition, the feasibility and effectiveness of Self-Aided SINS based on horizontal circular motion is also verified by field test with real IMU data. |
topic |
HOV SINS DVL midwater navigation self-aided SINS |
url |
https://ieeexplore.ieee.org/document/9389537/ |
work_keys_str_mv |
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