Real Time Implementation of Map Aided Positioning Using a Bayesian Approach
Independent thesis Basic level (professional degree)Student thesisAlternative title
Realtidsimplementation av kartstödd positionering med hjälp av Bayesianska estimeringsmetoder (Swedish)
With the simple means of a digitized map and the wheel speed signals, it is possible to position a vehicle with an accuracy comparable to GPS. The positioning problem is a non-linear filtering problem and a particle filter has been applied to solve it. Two new approaches studied are the Auxiliary Particle Filter (APF), that aims at lowerering the variance of the error, and Rao-Blackwellization that exploits the linearities in the model. The results show that these methods require problems of higher complexity to fully utilize their advantages.
Another aspect in this thesis has been to handle off-road driving scenarios, using dead reckoning. An off road detection mechanism has been developed and the results show that off-road driving can be detected accurately. The algorithm has been successfully implemented on a hand-held computer by quantizing the particle filter while keeping good filter performance.
Place, publisher, year, edition, pages
Institutionen för systemteknik , 2002. , 66 p.
Reglerteknik, Rao-Blackwellization, Bayesian Estimation, Map Matching, Particle Filter, Monte Carlo Simulation, Positioning, Off-road Driving, Quantization, Fixed Point Arithmetics, Modeling.
IdentifiersURN: urn:nbn:se:liu:diva-1493OAI: oai:DiVA.org:liu-1493DiVA: diva2:18817