Abstract
Fusion between INS and DVL is commonly used in AUV navigation. In normal operating scenarios the navigation accuracy is satisfactory for the AUV to complete its goal. Yet, when operating in complex environments situations of partial or complete DVL outages may occur. In the latter, the navigation solution will depend only on the INS and will drift in time. To circumvent such situations, an algorithm to enable the estimation of the velocity vector in situations of complete DVL outages is proposed based on past DVL measurements. Both velocity estimation algorithm and its corresponding variance are analytically derived. Simulation and sea experiment are presented to show the benefits of using the proposed approach.
| Original language | English |
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| Title of host publication | 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728187570 |
| DOIs | |
| State | Published - 30 Sep 2020 |
| Event | 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020 - St Johns, Canada Duration: 30 Sep 2020 → 2 Oct 2020 |
Publication series
| Name | 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020 |
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Conference
| Conference | 2020 IEEE/OES Autonomous Underwater Vehicles Symposium, AUV 2020 |
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| Country/Territory | Canada |
| City | St Johns |
| Period | 30/09/20 → 2/10/20 |
Bibliographical note
Publisher Copyright:© 2020 IEEE.
Keywords
- Autonomous Underwater vehicle
- Doppler Velocity Log
- Extended Kalman Filter
- Inertial Navigation Systems
- Underwater navigation
ASJC Scopus subject areas
- Automotive Engineering
- Ocean Engineering
- Control and Optimization