摘要
In order to solve the problem of location privacy under big data and improve the user positioning experience,a new concept of anonymous crowdsourcing-based WLAN indoor localization is proposed by employing the Micro-Electro-Mechanical System(MEMS)motion sensors as well as WLAN module in off-the-shelf smartphones.First of all,the crowdsourced motion traces with similar Received Signal Strength(RSS)sequences are assembled into a motion graph.Second,the mobility map is constructed according to traces segmentation and clustering.Third,the pixel template matching is adopted to physically label the pre-constructed mobility map.Finally,the robust Extended Kalman Filter(EKF)is designed to perform localization by matching the newly-collected RSS measurements against the mobility map.The extensive experimental results show that the proposed approach is capable of constructing a physically-labeled mobility map from the sporadically-collected crowdsourced motion traces as well as achieving satisfactory localization accuracy in a cost-efficient manner.
基金
the National Natural Science Foundation of China(61771083,61704015)
Program for Changjiang Scholars and Innovative Research Team in University(IRT1299)
Special Fund of Chongqing Key Laboratory(CSTC),Fundamental and Frontier Research Project of Chongqing(cstc2017jcyjAX0380,cstc2015jcyjBX0065)
University Outstanding Achievement Transformation Project of Chongqing(KJZH17117)
Postgraduate Scientific Research and Innovation Project of Chongqing(CYS17221).
