A Nonlinear Filter Based on Fokker Planck Equation and MCMC Measurement Updates Conference Paper uri icon


  • This paper presents a nonlinear filter based on the Fokker-Planck equation (FPE) for uncertainty propagation, coupled with a fast measurement update step. The measurement update is implemented as a function approximation performed over a Markov chain Monte Carlo (MCMC) sample of the un-normalized posterior obtained from the Bayes rule. MCMC sampling also results in fast computation of the normalization factor of the posterior, which is typically a computationally heavy step. A previously developed semianalytical meshless tool is employed to solve FPE for high dimensional systems in real time. Performance of the filter is studied for dynamical systems with 2 and 4 dimensional state spaces. ©2010 IEEE.

author list (cited authors)

  • Kumar, M., & Chakravorty, S.

citation count

  • 3

publication date

  • December 2010