Improved Particle Filter For Nor-Linear Noisy Observation Series
Journal Title: International Journal of Engineering and Science Invention - Year 2018, Vol 7, Issue 10
Abstract
The particle filtering (PF) theory is a very method to denoise the non-linear disturbed signals. It could disposal signals with non-Gauss noise which can’t be done by Kalman filtering (KF). The theory is widely used in the field of chaos signal denoise and target identification. But as the observing time extend, the PF will have problems with sample degeneration weight degeneracy. The paper presents an adaptive weight particle filtering (AWPF) theory which selects the samples using self-adaptive weight method. It makes the fission from samples with high weight value. The approach improves the estimation accuracy without decreasing computing speed.
Authors and Affiliations
Yaoyao ZHU
Keywords
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