A Framework for Particle Filtering for Positioning, Navigation and Tracking
2001 (English)In: Proceedings of the 11th IEEE Signal Processing Workshop on Statistical Signal Processing, IEEE , 2001, 34-37 p.Conference paper (Refereed)
A framework for positioning, navigation and tracking problems using particle filters (recursive Monte Carlo methods) is developed. Automotive and airborne applications, approached in this framework, have proven a numerical advantage over classical Kalman filter based algorithms. Here the use of non-linear measurement models and non-Gaussian measurement noise is the main explanation for the improvement in accuracy, and models for relevant sensors are surveyed.
Place, publisher, year, edition, pages
IEEE , 2001. 34-37 p.
Navigation, Target tracking, Particle filter, Positioning
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-91141DOI: 10.1109/SSP.2001.955215ISBN: 0-7803-7011-2OAI: oai:DiVA.org:liu-91141DiVA: diva2:617715
11th IEEE Signal Processing Workshop on Statistical Signal Processing, 6-8 August 2001, Singapore, Singapore