基于行人航迹推算的室内定位算法研究
针对室内定位的实际应用需求,提出了基于行人航迹推算算法（PDR）的适用于手机采集数据的室内定位方法。不同于传统的数据采集方法,该种定位方法利用手机得到加速度、陀螺仪以及地磁原始数据,通过分析加速度信号实现步频探测和步长估计。利用扩展卡尔曼滤波器（EKF）融合各惯性传感器数据以提高方向角的解算精度。最后设计了基于Android平台的数据采集软件,可利用手机内置的传感器设备实现数据采集。经实验数据分析,该算法的定位精度优于2m,在实用的基础上具有较高的定位精度和较低的实现复杂度。...
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| Published in | 电子技术应用 Vol. 43; no. 4; pp. 86 - 89 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
桂林电子科技大学信息与通信学院,广西桂林,541004
2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0258-7998 |
| DOI | 10.16157/j.issn.0258-7998.2017.04.023 |
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| Summary: | 针对室内定位的实际应用需求,提出了基于行人航迹推算算法（PDR）的适用于手机采集数据的室内定位方法。不同于传统的数据采集方法,该种定位方法利用手机得到加速度、陀螺仪以及地磁原始数据,通过分析加速度信号实现步频探测和步长估计。利用扩展卡尔曼滤波器（EKF）融合各惯性传感器数据以提高方向角的解算精度。最后设计了基于Android平台的数据采集软件,可利用手机内置的传感器设备实现数据采集。经实验数据分析,该算法的定位精度优于2m,在实用的基础上具有较高的定位精度和较低的实现复杂度。 |
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| Bibliography: | Aiming to the practice demand of the indoor location service, a positioning algorithm with Pedestrian Dead Reckoning （PDR） that suits for collecting data by eellphone terminal is presented. Different from the traditional data collection, taking the orig- inal data by cellphone, then the acceleration signal is utilized to realize stride detection and step length estimation. Extended Kalman Filter（EKF） is used to fuse datas from inertial sensors to improve the calculating accuracy of heading direction. Finally, data acquisition software based on Android platform is successfully designed which utilize sensors built-in cellphone implementing data acquisition. By the analysis of experimental data, the positioning accuracy is better than 2 m, and the algorithm can successfully achieve the indoor positioning under the requirement of higher precision and lower implementing complexity. Wang Yana, Cai Chenglin, Li Simin, Yu Honggang （School of Information and Communication, Guilin University of Electronic Technology, Gu |
| ISSN: | 0258-7998 |
| DOI: | 10.16157/j.issn.0258-7998.2017.04.023 |