this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.
該程序為基于粒子濾波的一種新算法,綜合MCMC Bayesian Model Selection即MONTE CARLO馬爾克夫鏈的算法,用來實現目標跟蹤,多目標跟蹤,及視頻目標跟蹤及定位等,解決非線性問題的能力比卡爾曼濾波,EKF,UKF好多了,是我珍藏的好東西,現拿出來與大家共享,舍不得孩子套不著狼,希望大家相互支持,共同促進.
