Fundamental Filtering Limitations in Linear Non-Gaussian Systems
2005 (English)In: Proceedings of the 16th IFAC World Congress, 2005, 45-45 p.Conference paper (Refereed)
The Kalman filter is known to be the optimal linear filter for linear non-Gaussian systems. However, nonlinear filters such as Kalman filter banks and more recent numerical methods such as the particle filter are sometimes superior in performance. Here a procedure to a priori decide how much can be gained using nonlinear filters, without having to resort to Monte Carlo simulations, is outlined. The procedure is derived in terms of the posterior Cramér-Rao lower bound. Results are shown for a class of standard distributions and models in practice.
Place, publisher, year, edition, pages
2005. 45-45 p.
Kalman filters, Linear filters, Cramér-Rao lower bound, Nonlinear filters, Optimal filtering
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-30867DOI: 10.3182/20050703-6-CZ-1902.00046Local ID: 16527ISBN: 978-3-902661-75-3OAI: oai:DiVA.org:liu-30867DiVA: diva2:251690
16th IFAC World Congress, Prague, Czech Republic, July, 2005