Underwater Terrain Navigation Using Standard Sea Charts and Magnetic Field Maps
(2017) IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)- Abstract
- Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents... (More)
- Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents an implementation of the opposite, namely using low-resolution maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements. The results from the simulated tests, described in this paper, show that the position error is below 25m throughout the whole test, and that the mean of the error is below 13m, which in most cases would be accurate enough to use for navigation. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/75c9baea-085d-4be1-b053-c04d80e3b5c2
- author
- Lager, Mårten LU ; Topp, Elin Anna LU and Malec, Jacek LU
- organization
- alternative title
- Terrängnavigering i undervattensläge genom att använda standardsjökort och magnetkartor
- publishing date
- 2017-12-11
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Terrain Navigation, Particle Filter, positioning, AUV, Kalman Filter
- host publication
- 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)
- pages
- 7 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)
- conference location
- Daegu, Korea, Republic of
- conference dates
- 2017-11-16 - 2017-11-18
- external identifiers
-
- scopus:85042353142
- ISBN
- 978-1-5090-6063-4
- 978-1-5090-6064-1
- DOI
- 10.1109/MFI.2017.8170410
- project
- Digital Cognitive Companion for Marine Vessels
- language
- English
- LU publication?
- yes
- id
- 75c9baea-085d-4be1-b053-c04d80e3b5c2
- date added to LUP
- 2017-10-04 14:51:55
- date last changed
- 2024-09-02 08:23:18
@inproceedings{75c9baea-085d-4be1-b053-c04d80e3b5c2, abstract = {{Many ships today rely on Global Navigation Satellite Systems (GNSS), for their navigation, where GPS (Global Positioning System) is the most well-known. Unfortunately, the GNSS systems make the ships dependent on external systems, which can be malfunctioning, be jammed or be spoofed. There are today some proposed techniques where, e.g., bottom depth measurements are compared with known maps using Bayesian calculations, which results in a position estimation. Both maps and navigational sensor equipment are used in these techniques, most often relying on high-resolution maps, with the accuracy of the navigational sensors being less important. Instead of relying on high-resolution maps and low accuracy navigation sensors, this paper presents an implementation of the opposite, namely using low-resolution maps, but compensating this by using high accuracy navigational sensors and fusing data from both bottom depth measurements and magnetic field measurements. The results from the simulated tests, described in this paper, show that the position error is below 25m throughout the whole test, and that the mean of the error is below 13m, which in most cases would be accurate enough to use for navigation.}}, author = {{Lager, Mårten and Topp, Elin Anna and Malec, Jacek}}, booktitle = {{2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)}}, isbn = {{978-1-5090-6063-4}}, keywords = {{Terrain Navigation; Particle Filter; positioning; AUV; Kalman Filter}}, language = {{eng}}, month = {{12}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{Underwater Terrain Navigation Using Standard Sea Charts and Magnetic Field Maps}}, url = {{http://dx.doi.org/10.1109/MFI.2017.8170410}}, doi = {{10.1109/MFI.2017.8170410}}, year = {{2017}}, }