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基于智能手机的地磁/WiFi/PDR的室内定位算法
引用本文:阮琨,王玫,罗丽燕,熊璐琦,宋浠瑜.基于智能手机的地磁/WiFi/PDR的室内定位算法[J].计算机应用,2018,38(9):2598-2602.
作者姓名:阮琨  王玫  罗丽燕  熊璐琦  宋浠瑜
作者单位:1. 认知无线电与信息处理省部共建教育部重点实验室(桂林电子科技大学), 广西 桂林 541004;2. 桂林电子科技大学 广西信息科学实验中心, 广西 桂林 541004
基金项目:国家自然科学基金资助项目(61771151);广西信息科学实验中心平台建设项目(PT1604);广西自然科学基金资助项目(2016GXNSFBA38014);中国博士后科学基金资助项目(2016M602921XB);广西高校无人机遥测重点实验室开放基金资助项目(WRJ2016KF01);广西研究生教育创新计划资助项目(YCSW2017137)。
摘    要:针对地磁指纹在室内定位中存在重复性,以及行人航迹推算(PDR)累积误差明显的问题,提出了一种基于智能手机的多传感器融合定位方法。该方法首先通过WiFi和随机采样一致性(RANSAC)算法拟合路径,确定初始位置;然后利用手机中的加速度计进行步长估计,利用陀螺仪进行转向检测;最后通过地图约束的自适应粒子滤波(PF)算法以地磁场修正PDR的定位结果。仿真结果表明,该方法能够有效克服PDR的累积误差以及地磁值不唯一的缺陷,提高室内定位精度、减少能耗。

关 键 词:室内定位  地磁  行人航迹推算  粒子滤波  初始位置  
收稿时间:2018-02-22
修稿时间:2018-04-20

Indoor localization algorithm based on geomagnetic field/WiFi/PDR of smartphone
RUAN Kun,WANG Mei,LUO Liyan,XIONG Luqi,SONG Xiyu.Indoor localization algorithm based on geomagnetic field/WiFi/PDR of smartphone[J].journal of Computer Applications,2018,38(9):2598-2602.
Authors:RUAN Kun  WANG Mei  LUO Liyan  XIONG Luqi  SONG Xiyu
Affiliation:1. Key Laboratory of Cognitive Radio and Information Processing of Ministry of Education(Guilin University of Electronic Technology), Guilin Guangxi 541004, China;2. Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
Abstract:Focusing on the repetitiveness of geomagnetic fingerprints and accumulated error in Pedestrian Dead Reckoning (PDR), a fusion indoor localization method was proposed by using multiple sensors of smartphone. Firstly, WiFi and RANdom SAmple Consensus (RANSAC) algorithm were used to find initial positions of users. Then the step length was calculated by using the accelerometer of smartphone, and the conclusion of turn was given by gyroscope. Finally, the localization of PDR was corrected by means of geomagnetic field using map-constrained adaptive Particle Filter (PF), which is a high precision indoor localization method. The simulation results show that the proposed method can effectively overcome the accumulated error of the PDR and the repetitiveness of geomagnetic values, improve the positioning accuracy and reduce the energy consumption.
Keywords:indoor localization                                                                                                                        geomagnetic                                                                                                                        Pedestrian Dead Reckoning (PDR)                                                                                                                        Particle Filter (PF)                                                                                                                        initial position
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