Particle filter algorithm has shown its good performance in non-linear and non-Gaussian models and is paid more and more attention.
粒子滤波算法由于其在非线性、非高斯模型中所表现出的优良性能，使得其越来越受到人们的重视。
My main work is applying the particle filter algorithm to random simulate the non-linear Bayesian dynamic models.
我的主要工作是把粒子滤波算法引人到非线性贝叶斯动态模型中来，对非线性模型进行了模拟。
Since the real life systems basically are nonlinear, so this paper study the basic principles and specific applications of Particle Filter (PF) specially used for non-linear non-Gaussian tracking.
由于我们实际生活中的系统基本上都是非线性的，因此本文研究的是专门用于非线性非高斯系统跟踪的粒子滤波算法(PF)的基本原理及其具体应用。
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