Particle estimation algorithm using angle between observation vectors for nonlinear system state

Jun Liang; Yu Peng; Xiyuan Peng

Particle estimation algorithm using angle between observation vectors for nonlinear system state

Jun Liang^*, Yu Peng, Xiyuan Peng

^*此作品的通讯作者

Harbin Institute of Technology

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

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).

源语言	英语
页（从-至）	700-702
页数	3
期刊	Chinese Journal of Electronics
卷	18
期	4
出版状态	已出版 - 10月 2009
已对外发布	是

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Liang, J., Peng, Y., & Peng, X. (2009). Particle estimation algorithm using angle between observation vectors for nonlinear system state. Chinese Journal of Electronics, 18(4), 700-702.

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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",

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Particle estimation algorithm using angle between observation vectors for nonlinear system state

摘要

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