A New Particle Filter Based on Numerical Integration Method
一种新的基于数值积分的粒子滤波算法

This paper introduces a new particle filter for nonlinear and non-Gaussian systems.The divided difference filter based on numerical integration is used for generating the importance density functions.As it integrates the new observations into system state transition density, which approximates to the state posterior density, the proposed particle filter has the better performance than the conventional one. Finally, the validity of this method is well verified by the computer simulations.