On this basis a nonlinear filtering technique of sequential Monte Carlo particle filter based on Bayesian approach is emphatically disussed which the posterior distribution of the state variables can be represented by a set of weighted particles, so the m
On this basis a nonlinear filtering technique of sequential Monte Carlo particle filter based on Bayesian approach is emphatically disussed which the posterior distribution of the state variables can be represented by a set of weighted particles, so the m
在此基础上重点论述了一种基于贝叶斯原理的序贯蒙特卡罗粒子滤波技术，该方法通过粒子的加权和表征后验概率密度，获得状态估值，在处理非线性非高斯系统的状态估计问题时精度逼近最优，鲁棒性更好。