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Particle-filter-matlab

于 2012-09-05 发布 文件大小:2KB
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  粒子滤波matlab仿真程序.粒子滤波的基本思想是:首先依据系统状态向量的经验条件分布,在状态空间抽样产生一组随机样本集合,这些样本集合称为粒子;然后根据观测值不断调整粒子的权重大小和样本位置;最后通过调整后的粒子信息修正最初的的经验条件分布,估计出系统状态和参数。该算法是一种递推滤波算法,可以用来估计任意非线性非高斯随机系统的状态和参数。 粒子滤波主要有三步基本操作:采样(从不含观察值的状态空间产生新的粒子)、权值计算(根据观察值计算各个粒子的权值)、重采样(抛弃权值小的粒子,使用权值大的粒子代替),这三步构成了粒子滤波的基本算法。 SIRF(Sample Importance Resampling Filter)算法是粒子滤波的一种基本算法。(Particle filter matlab simulation program)

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