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Bayesian Surface and Underwater Navigation
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, The Institute of Technology.
2004 (English)Report (Other academic)
Abstract [en]

A common framework for maritime surface and underwater (UW) map-aided navigation is proposed as a supplement to satellite navigation based on the global positioning system (GPS). The proposed Bayesian navigation method is based on information from a distance measuring equipment (DME) which is compared with the information obtained from various databases. As a solution to the recursive Bayesian navigation problem, the particle filter is proposed. For the described system, the fundamental navigation performance expressed as the Crameacuter-Rao lower bound (CRLB) is analyzed and an analytic solution as a function of the position is derived. Two detailed examples of different navigation applications are discussed: surface navigation using a radar sensor and a digital sea chart and UW navigation using a sonar sensor and a depth database. In extensive Monte Carlo simulations, the performance is shown to be close to the CRLB. The estimation performance for the surface navigation application is in comparison with usual GPS performance. Experimental data are also successfully applied to the UW application.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2004. , p. 10
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2649
Keywords [en]
Cramér-Rao lower bound, Particle filter, Recursive Bayesian estimation, Sea navigation
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:liu:diva-56008ISRN: LiTH-ISY-R-2649OAI: oai:DiVA.org:liu-56008DiVA, id: diva2:316723
Available from: 2010-04-30 Created: 2010-04-30 Last updated: 2014-08-13Bibliographically approved

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Karlsson, RickardGustafsson, Fredrik

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Output format
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