计算机科学 ›› 2017, Vol. 44 ›› Issue (8): 64-70.doi: 10.11896/j.issn.1002-137X.2017.08.012

• 网络与通信 • 上一篇    下一篇

基于众包的嵌套流形匹配室内定位方法

周阿鹏,覃锡忠,贾振红,NIKOLA Kasabov   

  1. 新疆大学信息科学与工程学院 乌鲁木齐830046,新疆大学信息科学与工程学院 乌鲁木齐830046,新疆大学信息科学与工程学院 乌鲁木齐830046,奥克兰理工大学知识工程与发现研究所 奥克兰1020
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受中国移动通信集团新疆有限公司研究发展基金项目(XJM2013-01),教育部促进与美大地区科研合作与高层次人才培养项目(2014-2029)资助

Crowdsourcing-based Indoor Localization via Embedded Manifold Matching

ZHOU A-peng, QIN Xi-zhong, JIA Zhen-hong and NIKOLA Kasabov   

  • Online:2018-11-13 Published:2018-11-13

摘要: 随着普适应用的兴起,室内定位变得越来越重要。传统的基于指纹的定位方法需要现场勘测,所需时间及工作量巨大,且需实时更新,以适应室内变化,这大大限制了其应用范围。采用众包形式进行室内信息采集,并记录其在室内的大量路径信息,利用嵌套在路径中的低维流形一致性进行地理位置匹配,以建立位置指纹库。通过高斯粒子滤波器对传感器数据进行去噪,进而解决步长差异问题。定位时,根据用户位置的连续性和路径信息筛选出合理的近邻点,继而实现精确定位。在84m2的会议室进行实验,在不需要现场勘测的情况下,所提方法可达到与传统方法可比的定位精度。该方法可以实时适应环境变化,在2周甚至1个月之后,其定位准确性优于传统定位方法。

关键词: 室内定位,众包,嵌套流形,高斯粒子滤波,步长差异

Abstract: With the boom of pervasive applications,indoor localization becomes more and more important.The traditionalfingerprint based positioning method requires the site survey in which the required time and workload are huge and the real-time updating needs to adapt to the changes in the room.All these factors greatly limit its scope of application.Therefore,the form of crowdsourcing was utilized to collect indoor information and record a large number of path information.The consistency of the low dimensional embedded manifold in the path were used for geographical position matching in order to establish the database of location fingerprints.Gauss particle filter denoising sensor data were used to further solve the problem of pedestrian step difference.According to the continuity of the user’s location and the path information,the reasonable nearest neighbor points were selected,and the accurate positioning was realized.The experiments have been carried out in the meeting room of 84m2,and the experiments can achieve comparable accuracy to the traditional method.The proposed method can adapt to the environmental changes in real time,and the positioning accuracy is better than the traditional positioning method after 2 weeks and even after 1 month.

Key words: Indoor localization,Crowdsourcing,Embedded manifold,Gauss particle filter,Pedestrian step difference

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