Adaptive MCMC Particle Filter for Tracking Maneuvering Target
When a target performs maneuvering movements,the targets state variables,such as position and velocity,vary and are not restricted to a xed dynamic model.New features of posterior distribution of the target state are encountered during the tracking process.In the MCMC based particle lter methods,the particles are moved towards the target posterior distribution to adapt to the new features formed during the tracking process.However,the traditional MCMC sampling needs a lot of iterations to converge to the target posterior distribution,which is very slow and not suitable for real-time tracking problem.In order to speed the convergence rate,a new method named adaptive MCMC based particle lter method,which is the combination of the adaptive Metropolis (AM)method and the importance sampling method,is proposed to tackle the real-time tracking problem.
LIU Jing HAN ChongZhao HU Yu
School of Electronics and Information Engineering,Xi ’an JiaoTong University,Xi ’an 710049,P.R.China Schools of Aeronautics,Northwestern Polytechnical University,P.R.China 710072
国际会议
The 30th Chinese Control Conference(第三十届中国控制会议)
烟台
英文
1-6
2011-07-01（万方平台首次上网日期，不代表论文的发表时间）