KALMAN FILTER ALGORITHM

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引用次数: 1

Abstract

This section covers the Kalman Filter Algorithm. First we'll cover the State Space format of modeling and measuring a discrete-time dynamic system of estimated states, noisy inputs, and noisy measurements. Second, we'll explore all the different pieces of information about our system necessary to inform the algorithm. Third, the specific Kalman Filter Algorithm constructed based off of those parameters. Finally, we'll use some example state spaces and measurements to see how well we track.
卡尔曼滤波算法
本节介绍卡尔曼滤波算法。首先,我们将介绍对估计状态、噪声输入和噪声测量的离散时间动态系统进行建模和测量的状态空间格式。其次,我们将探索系统中所有不同的信息片段,这些信息片段是为算法提供信息所必需的。第三,基于这些参数构造具体的卡尔曼滤波算法。最后,我们将使用一些状态空间和度量示例来查看跟踪效果。
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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