Sequential Monte Carlo Filtering Techniques Applied to Integrated Navigation Systems
2001 (English)In: Proceedings of the 2001 American Control Conference, 2001, 4375-4380 vol.6 p.Conference paper (Refereed)
This paper addresses the problem of integrated aircraft navigation, more specifically how to integrate inertial navigation with terrain aided positioning. This is a highly nonlinear and non-Gaussian recursive state estimation problem which requires state of the art methods. We propose an algorithm based on the particle filter with particular attention to the complexity of the problem. The proposed algorithm takes advantage of linear and Gaussian structure within the system and solves these parts using the Kalman filter. The remaining parts suffering from severe nonlinear and/or non-Gaussian structure are solved using the particle filter. The proposed filter is applied to a simplified integrated navigation system. The result shows that very good performance is achieved for a tractable computational load.
Place, publisher, year, edition, pages
2001. 4375-4380 vol.6 p.
Gaussian processes, Kalman filters, Aircraft navigation, State estimation
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-90800DOI: 10.1109/ACC.2001.945666ISBN: 0-7803-6495-3OAI: oai:DiVA.org:liu-90800DiVA: diva2:616423
2001 American Control Conference, Arlington, VA, USA, June, 2001