A New Multisensor Particle Filter Method
Wei Xiong, Jingwei Zhang, You He, Zhenyu Song · 2005
Multisensor state estimation is an important issue in multisensor data fusion. In order to solve the centralized multisensor sate estimation problem of non-Gaussian nonlinear system, the paper proposes a new multisensor sequential particle filter (MSPF). First, the general theoretical model of centralized multisensor particle filter is got. Then, a sequential resampling method is proposed according to the characteristics of centralized multisensor system. At last, a Monte Carlo simulation is used to analyze the performance of the method. The results of the simulation show that the new method can greatly improve the state estimation precision of multisensor system. Moreover, it will get more accurate estimation with the increase of sensor numbers.