Sequential Monte Carlo: A Unified Review

IF 11.2 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
A. Wills, Thomas Bo Schön
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引用次数: 3

Abstract

Sequential Monte Carlo methods—also known as particle filters—offer approximate solutions to filtering problems for nonlinear state-space systems. These filtering problems are notoriously difficult to solve in general due to a lack of closed-form expressions and challenging expectation integrals. The essential idea behind particle filters is to employ Monte Carlo integration techniques in order to ameliorate both of these challenges. This article presents an intuitive introduction to the main particle filter ideas and then unifies three commonly employed particle filtering algorithms. This unified approach relies on a nonstandard presentation of the particle filter, which has the advantage of highlighting precisely where the differences between these algorithms stem from. Some relevant extensions and successful application domains of the particle filter are also presented. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 14 is May 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
顺序蒙特卡罗:一个统一的回顾
顺序蒙特卡罗方法-也被称为粒子滤波器-为非线性状态空间系统的滤波问题提供了近似的解决方案。由于缺乏封闭形式的表达式和具有挑战性的期望积分,这些过滤问题通常很难解决。粒子滤波器背后的基本思想是采用蒙特卡罗积分技术,以改善这两个挑战。本文直观地介绍了粒子滤波的主要思想,并对三种常用的粒子滤波算法进行了统一。这种统一的方法依赖于粒子滤波器的非标准表示,其优点是可以精确地突出这些算法之间的差异。文中还介绍了粒子滤波的一些相关扩展和成功应用领域。预计《控制、机器人和自主系统年度评论》第14卷的最终在线出版日期是2023年5月。修订后的估计数请参阅http://www.annualreviews.org/page/journal/pubdates。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
28.30
自引率
2.20%
发文量
25
期刊介绍: The Annual Review of Control, Robotics, and Autonomous Systems offers comprehensive reviews on theoretical and applied developments influencing autonomous and semiautonomous systems engineering. Major areas covered include control, robotics, mechanics, optimization, communication, information theory, machine learning, computing, and signal processing. The journal extends its reach beyond engineering to intersect with fields like biology, neuroscience, and human behavioral sciences. The current volume has transitioned to open access through the Subscribe to Open program, with all articles published under a CC BY license.
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