Non-GNSS Smartphone Pedestrian Navigation Using Barometric Elevation and Digital Map-Matching

Sensors

John Raquet¹  Daniel Broyles¹  Kyle Kauffman¹  Piotr Smagowski² 

[1] Air Force Institute of Technology, 2950 Hobson Way, Wright-Patterson AFB, OH 45433-7765, USA;Military Institute of Armament Technology, 05-220 Zielonka, Poland;

关键词: smartphone sensor fusion;    particle filter;    pedestrian dead reckoning;    map-matching;   

DOI  :  10.3390/s18072232

来源: DOAJ

【 摘 要 】

Pedestrian navigation in outdoor environments where global navigation satellite systems (GNSS) are unavailable is a challenging problem. Existing technologies that have attempted to address this problemoften require external reference signals or specialized hardware, the extra size,weight, power, and cost of which are unsuitable for many applications. This article presents a real-time, self-contained outdoor navigation application that uses only the existing sensors on a smartphone in conjunction with a preloaded digital elevation map. The core algorithm implements a particle filter, which fuses sensor data with a stochastic pedestrian motion model to predict the user’s position. The smartphone’s barometric elevation is then compared with the elevation map to constrain the position estimate. The system developed for this research was deployed on Android smartphones and tested in several terrains using a variety of elevation data sources. The results fromthese experiments showthe systemachieves positioning accuracies in the tens of meters that do not grow as a function of time

【 授权许可】

Unknown