惯性导航系统
惯性测量装置
航位推算
惯性基准装置
卡尔曼滤波器
风三角
保险丝(电气)
不可见的
计算机科学
惯性参考系
计量单位
行人
计算机视觉
人工智能
模拟
工程类
全球定位系统
移动机器人
电信
机器人
数学
物理
电气工程
计量经济学
机器人控制
量子力学
运输工程
作者
Andrei M. Shkel,Yusheng Wang
标识
DOI:10.1002/9781119699910.ch5
摘要
This chapter focuses on the self-contained aiding techniques for pedestrian inertial navigation, which can limit the navigation error propagation of the strapdown inertial navigation while keeping the whole system independent of the environment. One of the most commonly used aiding techniques in the pedestrian inertial navigation is the Zero-Velocity Update (ZUPT) aiding. One of the main advantages of ZUPT is its ability to obtain pseudo-measurement of the velocity, which is otherwise unobservable by inertial measurement units (IMUs). There are two key parts involved in the ZUPT-aided navigation algorithm: the stance phase detector and the pseudo-measurement of the motion of the foot. In the pedestrian inertial navigation, the Extended Kalman Filter is commonly used to fuse the IMU readouts with other aiding techniques to obtain a more accurate navigation result. The chapter introduces the concept, algorithmic implementation, and parameter selection of the ZUPT-aided pedestrian inertial navigation.
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