A Tutorial on Particle Filtering and Smoothing: Fifteen years later
A Tutorial on Particle Filtering and Smoothing: Fifteen years later
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发表时间：
2008
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通讯作者：
A. Doucet;A. M. Johansen
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作者：
A. Doucet;A. M. Johansen
非线性非高斯状态空间模型的最优估计问题通常不允许解析解。自1993年引入以来，粒子滤波方法已经成为一类非常流行的算法，以在线方式解决这些估计问题，即随着观测结果的可用而递归地解决这些问题，并且现在通常用于计算机视觉，计量经济学，机器人和导航等领域。本教程的目的是提供一个完整的，最新的调查，这一领域的2008年。基本和先进的粒子滤波方法以及平滑。
Optimal estimation problems for non-linear non-Gaussian state-space models do not typically admit analytic solutions. Since their introduction in 1993, particle filtering methods have become a very popular class of algorithms to solve these estimation problems numerically in an online manner, i.e. recursively as observations become available, and are now routinely used in fields as diverse as computer vision, econometrics, robotics and navigation. The objective of this tutorial is to provide a complete, up-to-date survey of this field as of 2008. Basic and advanced particle methods for filtering as well as smoothing are presented.