Introduction - If you have any usage issues, please Google them yourself
With the years the level of computer hardware development, the speed of calculation, derived from the sequence of the Monte Carlo method, Monte Carlo particle filter method applied research has once again become active again. In this paper, this kind of Monte Carlo particle filter is to use the concept of sequence of the importance of sampling, using a series of discrete random sample with weights similar to the corresponding probability density function. Since the particle filtering method is not as broad as Kalman filtering method for nonlinear system to do linear approximation, nonlinear state estimation in the generalized Kalman filter than an advantage. Applications in many areas has been gradually generalized Kalman filter has an alternative trend.