Knowledge-based error detection and correction method of a Multi-sensor Multi-network positioning platform for pedestrian indoor navigation

Yuwei Chen, Ruizhi Chen, L. Pei, T. Kroger, H. Kuusniemi, Jingbin Liu, Wei Chen
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引用次数: 34

Abstract

For pedestrian indoor navigation, an accurate 2D/3D position is a premise for any further processing. Currently, indoor navigation is a challenging task for standalone GNSS technology. FGI has integrated self-contained sensors with wireless locating technology to investigate a hybrid indoor positioning solution. However, the infrastructure indoors inflicts multiple disturbances to the positioning sensors. A knowledge-based error detection and correction method is applied to detect and eliminate the occurring gross errors. Six modes of user dynamics are extracted from measurements of a barometer and an accelerometer, and such contexts can improve the positioning accuracy and enhance the user experience of the final navigation application.
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行人室内导航多传感器多网络定位平台基于知识的误差检测与校正方法
对于行人室内导航,精确的2D/3D位置是任何进一步处理的前提。目前,室内导航对于独立GNSS技术来说是一项具有挑战性的任务。FGI将独立传感器与无线定位技术集成在一起,研究一种混合室内定位解决方案。然而,室内基础设施会对定位传感器造成多重干扰。提出了一种基于知识的误差检测与校正方法来检测和消除出现的严重误差。从气压计和加速度计的测量数据中提取了6种用户动态模式,这些情境可以提高定位精度,增强最终导航应用的用户体验。
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