TY - GEN

T1 - Direct versus prediction-based particle filter algorithms

AU - Desbouvries, François

AU - Ait-El-Fquih, Boujemaa

PY - 2008

Y1 - 2008

N2 - Particle Filtering (PF) algorithms propagate in time a Monte Carlo (MC) approximation of the a posteriori filtering measure in a Hidden Markov Chain (HMC) model. In this paper we first shed some new light on two classical PF algorithms, which can be considered as natural MC implementations of two two-step direct recursive formulas for computing the filtering distribution. We next address the Particle Prediction (PP) problem, which happens to be simpler than the PF problem because the optimal prediction conditional importance distribution (CID) is much easier to sample from. Motivated by this result we finally develop two PP-based PF algorithms, and we compare our algorithms via simulations.

AB - Particle Filtering (PF) algorithms propagate in time a Monte Carlo (MC) approximation of the a posteriori filtering measure in a Hidden Markov Chain (HMC) model. In this paper we first shed some new light on two classical PF algorithms, which can be considered as natural MC implementations of two two-step direct recursive formulas for computing the filtering distribution. We next address the Particle Prediction (PP) problem, which happens to be simpler than the PF problem because the optimal prediction conditional importance distribution (CID) is much easier to sample from. Motivated by this result we finally develop two PP-based PF algorithms, and we compare our algorithms via simulations.

KW - Hidden Markov chains

KW - Optimal importance function

KW - Particle filtering

KW - Sampling importance resampling

KW - Sequential importance sampling

UR - http://www.scopus.com/inward/record.url?scp=58049184929&partnerID=8YFLogxK

U2 - 10.1109/MLSP.2008.4685497

DO - 10.1109/MLSP.2008.4685497

M3 - Conference contribution

AN - SCOPUS:58049184929

SN - 9781424423767

T3 - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

SP - 303

EP - 308

BT - Proceedings of the 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

T2 - 2008 IEEE Workshop on Machine Learning for Signal Processing, MLSP 2008

Y2 - 16 October 2008 through 19 October 2008

ER -