Mobile localization with NLOS mitigation using improved Rao-Blackwellized Particle Filtering algorithm

Author

Liang, Chen ; Lenan, Wu

fYear

2009

fDate

25-28 May 2009

Firstpage

174

Lastpage

178

Abstract

An improved Rao-Blackwellized particle filtering (RBPF) is proposed track the mobility of mobile station (MS) in mixed line-of-sight (LOS) or non-line-of-sight (NLOS) conditions in cellular network. The algorithm first estimates the sight condition state using particle filtering method, in which particles are sampled by the optimal trial distribution and selected by one-step backward prediction. Then, by applying decentralized extended Kalman filter (EKF), the mobile state could then be analytically computed. Simulations show more accurate results can be achieved by the proposed method than by current methods.

Keywords

Kalman filters; cellular radio; particle filtering (numerical methods); radio direction-finding; signal sampling; Rao-Blackwellized particle filtering algorithm; cellular network; decentralized extended Kalman filter; mixed line-of-sight condition; mobile localization; mobile station; mobility tracking; nonline-of-sight condition; one-step backward prediction; optimal trial distribution; particle sampling; Consumer electronics; Electromagnetic scattering; Filtering algorithms; Kalman filters; Mobile computing; Particle tracking; Position measurement; State estimation; Testing; Time measurement; extended kalman filter (EKF); mobility localization; non-line-of-sight (NLOS); particle filter (PF);

fLanguage

English

Publisher

ieee

Conference_Titel

Consumer Electronics, 2009. ISCE '09. IEEE 13th International Symposium on

Conference_Location

Kyoto

Print_ISBN

978-1-4244-2975-2

Electronic_ISBN

978-1-4244-2976-9

Type

conf

DOI

10.1109/ISCE.2009.5157040

Filename

5157040