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Underwater Terrain Navigation Using Standard Sea Charts and Magnetic Field Maps

Lager, Mårten LU ; Topp, Elin Anna LU orcid and Malec, Jacek LU orcid (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:
author
; and
organization
alternative title
Terrängnavigering i undervattensläge genom att använda standardsjökort och magnetkartor
publishing date
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
2024-06-25 05:18:52
@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}},
}