Title :
Particle filter positioning and tracking based on dynamic model
Author :
Tian-Zengshan ; Luo Lei
Author_Institution :
Inst. of Wireless Location & Space Meas., Chongqing Univ. of Posts & Telecommun., Chongqing
Abstract :
In order to deal with mobile target tracking which contain non-linear and non-Gaussian problem, this paper presents a particle filter positioning and tracking algorithm based on dynamic model. This method can apply to any state-space model which is nonlinear system, and the accuracy can approach to best of all. The simulation showed that particle filter method can be used effectively to inhibit non-line-of-sight (NLOS) errors and can be combined with positioning and tracking model to get higher precision.
Keywords :
matrix algebra; motion estimation; nonlinear systems; particle filtering (numerical methods); state-space methods; target tracking; mobile target tracking; nonGaussian problem; nonline-of-sight errors; nonlinear problem; particle filter positioning; particle filter tracking; positioning; state-space model; Acceleration; Bayesian methods; Filtering; Kalman filters; Nonlinear dynamical systems; Nonlinear systems; Particle filters; Particle tracking; Real time systems; Target tracking;
Conference_Titel :
Automation Science and Engineering, 2008. CASE 2008. IEEE International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4244-2022-3
Electronic_ISBN :
978-1-4244-2023-0
DOI :
10.1109/COASE.2008.4626430
