Crowdsourcing and Multisource Fusion-Based Fingerprint Sensing in Smartphone Localization

Authors:
Open Access
Publisher website
Google Scholar
Abstract
Traditional WiFi fingerprint positioning normally uses a time consuming and labor intensive process called site survey. This paper proposes a crowdsourcing and multi-source fusion based fingerprint sensing (CMFS) to replace the traditional site survey approach. In CMFS, motion sensors are used to construct the radio map by volunteers and Pedestrian Dead Reckoning (PDR) based on motion sensors equipped in smartphones is used for positioning. In positioning phase, an Extended Kalman Filter (EKF) based multi-source fusion algorithm is further developed to tackle the nonlinear fusion so that both positioning accuracy and robustness can be improved. Both experimental and simulation results verify that the performance of proposed schemes is comparable to the traditional fingerprint approaches. Further the EKF based fusion scheme is found to improve smoothness and stability of CMFS greatly.
Funding Information
  • Provincial Natural Science Foundation of Heilongjiang (ZD2017013)
  • National Natural Science Foundation of China (61401119)
  • National Science Foundation NeTS Project (1423348)
  • National Science and Technology Major Project (2015ZX03004002-004)
  • Natural Science Foundation of Jiangsu Province (BK20171023)

This publication has 39 references indexed in Scilit: