Title :
A General Convergence Result for Particle Filtering
Author :
Xiao-Li Hu ; Schon, Thomas ; Ljung, L.
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Univ. of Newcastle, Newcastle, NSW, Australia
fDate :
7/1/2011 12:00:00 AM
Abstract :
The particle filter has become an important tool in solving nonlinear filtering problems for dynamic systems. This correspondence extends our recent work, where we proved that the particle filter converges for unbounded functions, using L4-convergence. More specifically, the present contribution is that we prove that the particle filter converge for unbounded functions in the sense of Lp-convergence, for an arbitrary p ≥ 2.
Keywords :
convergence of numerical methods; nonlinear dynamical systems; nonlinear filters; particle filtering (numerical methods); L4-convergence; Lp-convergence; dynamic systems; nonlinear filtering problems; particle filtering; unbounded functions; Approximation methods; Convergence; Density measurement; Estimation; Markov processes; Noise measurement; Signal processing algorithms; Convergence of numerical methods; nonlinear estimation; particle filters; state estimation;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2011.2135349