Deterministic and Stochastic Bayesian Methods in Terrain Navigation
1998 (English)Report (Other academic)
Terrain navigation is an application where inference between conceptually different sensors is performed recursively online. In this work the Bayesian framework of statistical inference is applied to this recursive estimation problem. Three algorithms for approximative Bayesian estimation are evaluated in simulations, one deterministic algorithm and two stochastic. The deterministic method solve the Bayesian inference problem by numerical integration while the stochastic methods simulate several candidate solutions and evaluates the integral by averaging between these candidates. Simulations show that all three algorithms are efficient and approximately reach the Cramer-Rao bound. However, the stochastic methods are sensitive to outliers and the deterministic method has the limitation of being hard to implement in higher dimensions.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 1998. , 7 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2052
Simulation methods, Statistical interference, Bayesian framework, Recursive estimation, Cybernetik Informationsteori
IdentifiersURN: urn:nbn:se:liu:diva-55657ISRN: LiTH-ISY-R-2052OAI: oai:DiVA.org:liu-55657DiVA: diva2:316415