Particle estimation algorithm using correlation of observation for nonlinear system state

J. Liang; X. Y. Peng; Y. T. Ma

doi:10.1049/el:20080179

Particle estimation algorithm using correlation of observation for nonlinear system state

J. Liang^*
, X. Y. Peng
, Y. T. Ma

^*Corresponding author for this work

School of Electronics and Information Engineering

Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

10 Scopus citations

Abstract

A particle estimation algorithm, where the weight of the particle is proportional to the correlation coefficient of observations, is presented. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than SIR, APF, RPF, and GPF.

Original language	English
Pages (from-to)	553-555
Number of pages	3
Journal	Electronics Letters
Volume	44
Issue number	8
DOIs	https://doi.org/10.1049/el:20080179
State	Published - 2008

Access to Document

10.1049/el:20080179

Cite this

@article{1ede409fbf904c429f63fc3e034b11d2,

title = "Particle estimation algorithm using correlation of observation for nonlinear system state",

abstract = "A particle estimation algorithm, where the weight of the particle is proportional to the correlation coefficient of observations, is presented. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than SIR, APF, RPF, and GPF.",

author = "J. Liang and Peng, \{X. Y.\} and Ma, \{Y. T.\}",

year = "2008",

doi = "10.1049/el:20080179",

language = "英语",

volume = "44",

pages = "553--555",

journal = "Electronics Letters",

issn = "0013-5194",

publisher = "John Wiley \& Sons Inc.",

number = "8",

}

TY - JOUR

T1 - Particle estimation algorithm using correlation of observation for nonlinear system state

AU - Liang, J.

AU - Peng, X. Y.

AU - Ma, Y. T.

PY - 2008

Y1 - 2008

N2 - A particle estimation algorithm, where the weight of the particle is proportional to the correlation coefficient of observations, is presented. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than SIR, APF, RPF, and GPF.

AB - A particle estimation algorithm, where the weight of the particle is proportional to the correlation coefficient of observations, is presented. When the likelihood has a bimodal nature, this algorithm leads to more accurate state estimates than SIR, APF, RPF, and GPF.

UR - https://www.scopus.com/pages/publications/42149146772

U2 - 10.1049/el:20080179

DO - 10.1049/el:20080179

M3 - 文章

AN - SCOPUS:42149146772

SN - 0013-5194

VL - 44

SP - 553

EP - 555

JO - Electronics Letters

JF - Electronics Letters

IS - 8

ER -

Particle estimation algorithm using correlation of observation for nonlinear system state

Abstract

Access to Document

Other files and links

Fingerprint

Cite this