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。
Particle filter algorithm has shown its good performance in non-linear and non-Gaussian models and is paid more and more attention.
提出并设计了一种基于粒子群优化算法的振动信号的自适应滤波模型。该滤波模型在计算机仿真测试中，获得了很高的效率和良好的结果。
A new adaptive filtering model based on particle swarm optimization (PSO) algorithm is proposed and designed. It is proved to be efficient and effective in the computer simulation example test.
在估计目标状态时，采用了粒子滤波算法，设计了基于自适应表面模型的观测模型；
When estimating the target state, particle filter is adopted, and the observation model is designed based on the adaptive appearance model.
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