粒子滤波器是通过蒙特卡罗模拟来实现递归贝叶斯滤波，它不需要线性、高斯噪声的假设，适用于任何能用状态空间模型表示的非线性系统，比卡尔曼滤波器的适用范围广。这里给出了几个粒子滤波的matlab编程实例。-Particle filters are using Monte Carlo simulations to achieve the recursive Bayesian filtering, it does not require linear, Gaussian noise assumptions

标准粒子滤波目标跟踪源码！ 一维情况下 非线性非高斯,-Standard particle filter target tracking source! One-Dimensional Non-linear non-Gaussian,

用于目标跟踪的粒子滤波代码， 用matlab编写的，很有借鉴性，一维情况下，非高斯非线性，其中将扩展卡尔曼滤波与粒子滤波进行比较，更好的说明了粒子滤波的优越性-Particle filter for target tracking code, using matlab prepared very useful reference resistance, the one-dimensional case, the non-Gaussian nonlinear, which will be ex