个人信息Personal Information
副教授
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:控制科学与工程学院
学科:控制理论与控制工程. 模式识别与智能系统
电子邮箱:zhaohy@dlut.edu.cn
Smartphone-Based 3D Indoor Pedestrian Positioning through Multi-Modal Data Fusion
点击次数:
论文类型:期刊论文
发表时间:2019-10-02
发表刊物:SENSORS
收录刊物:PubMed、EI、SCIE
卷号:19
期号:20
关键字:pedestrian dead reckoning (PDR); indoor localization; pedestrian navigation; barometer; map matching; particle filter; gait analysis; inertial measurement unit (IMU); inertial sensor; inertial navigation system (INS)
摘要:Combining research areas of biomechanics and pedestrian dead reckoning (PDR) provides a very promising way for pedestrian positioning in environments where Global Positioning System (GPS) signals are degraded or unavailable. In recent years, the PDR systems based on a smartphone's built-in inertial sensors have attractedmuch attention in such environments. However, smartphone-basedPDR systems are facing various challenges, especially the heading drift, which leads to the phenomenon of estimated walking path passing through walls. In this paper, the 2D PDR system is implemented by using a pocket-worn smartphone, and then enhanced by introducing a map-matching algorithm that employs a particle filter to prevent the wall-crossing problem. In addition, to extend the PDR system for 3D applications, the smartphone's built-in barometer is used to measure the pressure variation associated to the pedestrian's vertical displacement. Experimental results show that the map-matching algorithm based on a particle filter can effectively solve the wall-crossing problem and improve the accuracy of indoor PDR. By fusing the barometer readings, the vertical displacement can be calculated to derive the floor transition information. Despite the inherent sensor noises and complex pedestrian movements, smartphone-based 3D pedestrian positioning systems have considerable potential for indoor location-based services (LBS).