Particle filtering with particle swarm optimization in systems with multiplicative noise
A. D. Klamargias, Konstantinos E. Parsopoulos, Ph. D. Alevizos, Michael N. Vrahatis · 2008
We propose a Particle Filter model that incorporates Particle Swarm Optimization for predicting systems with multiplicative noise. The proposed model employs a conventional multiobjective optimization approach to weight the likelihood and prior of the filter in order to alleviate the particle impoverishment problem. The resulting scheme is tested on a well-known test problem with multiplicative noise. Results are promising, especially in cases of high system and measurement noise levels.