Multiple Model Particle Filter based on Two Stage Prediction Update
会议名称：《2010 3rd IEEE International Conference on Computer Science and Information Technology—ICCSIT 2010》
会议日期：2010年
学科分类：080902[工学-电路与系统] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学]
基 金：supported by the key project of the National Natural Science Foundation of China(60634030) the National Natural Science Foundation of China (60702066)
关 键 词：multiple model particle filter proposal distribution particle degeneracy particles impoverishments
摘 要：正Aiming at the particle degeneracy caused by the introduction of model information in particle sampling process, a novel multiple model particle filtering algorithm based on two stage prediction update is *** the multiple model particle filtering framework,the dynamic combination of the prediction and update mechanism of particle filter and Kalman filter is realized by the reasonable arrangement of the following four steps including importance sampling,one-step prediction,re-sampling and observation *** the filter gain calculated by one-step prediction and observation update mechanism of Kalman filter,is used to directly optimize state estimation and avoids the loss of the latest observation and original particle information in filtering *** addition,a new promoting strategy of particles diversity is given to resolve particles impoverishments by means of the current state *** theoretical analysis and experimental results show that the filtering precision is improved significantly with appropriately increasing computational burden.