NDLI: Particle filtering and Cramer-Rao lower bound for underwater navigation

Content Provider	IEEE Xplore Digital Library
Author	Karlsson, R. Gusfafsson, F. Karlsson, T.
Copyright Year	2003
Description	Author affiliation: Dept. of Electr. Eng., Linkoping Univ., Sweden (Karlsson, R.; Gusfafsson, F.)
Abstract	We have studied a sea navigation method relying on a digital underwater terrain map and sonar measurements. The method is applicable for both ships and underwater vessels. We have used experimental data to build an underwater map and to investigate the estimation performance. Since the problem is non-linear, due to the measurement relation, we apply a sequential Monte Carlo method, or particle filter, for the state estimation. The fundamental limitations in navigation uncertainty can be described in terms of the Cramer-Rao lower bound, which is interpreted in terms of the inertial navigation system (INS) error, the sensor accuracy and the terrain map excitation. Hence, the Cramer-Rao lower bound can be interpreted and used in the design for INS systems, sensor performance or, if these are given, how much terrain or depth excitation that is needed for use in positioning and navigation.
Sponsorship	IEEE Signal Process, Soc
File Size	268416
File Format	PDF
ISBN	0780376633
ISSN	15206149
DOI	10.1109/ICASSP.2003.1201619
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-04-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Filtering Sonar navigation Sensor systems Sonar measurements Marine vehicles Sea measurements Particle measurements Particle filters State estimation Inertial navigation
Content Type	Text
Resource Type	Article

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