Pedestrian inertial navigation: An overview of model and data-driven approaches

被引：0
|
作者：
Klein, Itzik [1 ]
机构：
[1] Univ Haifa, Charney Sch Marine Sci, Hatter Dept Marine Technol, Autonomous Nav & Sensor Fus Lab, Haifa, Israel
来源：
RESULTS IN ENGINEERING | 2025年 / 25卷
关键词：
Pedestrian dead reckoning; Inertial sensors; Machine learning; ZERO-VELOCITY DETECTION; STEP-LENGTH ESTIMATION; SMARTPHONE; ATTITUDE; ACCELEROMETER; MOVEMENT; SYSTEMS;
D O I：
10.1016/j.rineng.2025.104077
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The task of indoor positioning is fundamental to several applications, including navigation, healthcare, location- based services, and security. An emerging field is inertial navigation for pedestrians, which relies only on inertial sensors for positioning. In this paper, we present inertial pedestrian navigation models and learning approaches. Among these, are methods and algorithms for shoe-mounted inertial sensors and pedestrian dead reckoning (PDR) with unconstrained inertial sensors. We also address three categories of data-driven PDR strategies: activity- assisted, hybrid approaches, and learning-based frameworks.
引用
收藏
页数：12
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