@article{59bc1d009929411ba40ca84e7a7530d2,
title = "Particle estimation algorithm using angle between observation vectors for nonlinear system state",
abstract = "A particle estimation algorithm where the weight of the particle is related to angle between observation vectors is presented for nonliear system state. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than Sequential importance resampling (SIR), Auxiliary particle filter (APF), Regularized particle filter (RPF), and Gaussian particle filter (GPF).",
keywords = "Auxiliary particle filter (APF), Gaussian particle filter (GPF), Nonliear system, Particle alter, Regularized particle filter (RPF), Sequential importance resampling (SIR), State estimation",
author = "Jun Liang and Yu Peng and Xiyuan Peng",
year = "2009",
month = oct,
language = "English",
volume = "18",
pages = "700--702",
journal = "Chinese Journal of Electronics",
issn = "1022-4653",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "4",
}