Introduces the Kalman filter as a method that can solve problems related to estimating the hidden internal state of a dynamic system. Develops the background theoretical topics in state-space models and stochastic systems. Presents the steps of the linear Kalman filter and shows how to implement these steps in Octave code and how to evaluate the filter’s output.
Kalman Filter Boot Camp (and State Estimation)
Kalman Filter Boot Camp (and State Estimation)
本课程是 Applied Kalman Filtering 专项课程 的一部分
位教师：Gregory Plett
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本课程是 Applied Kalman Filtering 专项课程 专项课程的一部分
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该课程共有4个模块
This week, you will learn what a Kalman filter is and generally what it does. You will be introduced to the roadmap for the course and the specialization, and will learn some applications that use Kalman filters.
涵盖的内容
6个视频11篇阅读材料6个作业1个讨论话题
Kalman filters estimate the "state" of a system that is described using a "state-space model." This week, you will learn the background concepts in state-space models that are required in order to implement a Kalman filter.
涵盖的内容
8个视频9篇阅读材料8个作业2个非评分实验室
Systems whose state we would like to estimate are affected by unknown inputs ("disturbances" or "process noises") and their measurements are affected by sensor noises. These noises are modeled by random variables. This week, you will learn the background concepts in random variables that are required in order to implement a Kalman filter.
涵盖的内容
8个视频8篇阅读材料8个作业1个非评分实验室
Even though we have not yet derived the steps of the Kalman filter, it is instructive to gain insight into a Kalman filter's operation by watching it run. This week, you will learn how to implement a Kalman filter in Octave and see cases where it works well and where it fails (next course, you will learn why!).
涵盖的内容
6个视频6篇阅读材料6个作业4个非评分实验室
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位教师
授课教师评分
5.0 (10个评价)
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学生评论
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RP
5
已于 Mar 29, 2025审阅
Outstanding introduction to Kalman Filtering. A very well designed course. Thanks to Professor Platt.
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