title: A Crowd-Sourcing Indoor Localization Algorithm via Optical Camera on a Smartphone Assisted by Wi-Fi Fingerprint RSSI.
abstract: Indoor positioning based on existing Wi-Fi fingerprints is becoming more and more common. Unfortunately, the Wi-Fi fingerprint is susceptible to multiple path interferences, signal attenuation, and environmental changes, which leads to low accuracy. Meanwhile, with the recent advances in charge-coupled device (CCD) technologies and the processing speed of smartphones, indoor positioning using the optical camera on a smartphone has become an attractive research topic; however, the major challenge is its high computational complexity; as a result, real-time positioning cannot be achieved. In this paper we introduce a crowd-sourcing indoor localization algorithm via an optical camera and orientation sensor on a smartphone to address these issues. First, we use Wi-Fi fingerprint based on the K Weighted Nearest Neighbor (KWNN) algorithm to make a coarse estimation. Second, we adopt a mean-weighted exponent algorithm to fuse optical image features and orientation sensor data as well as KWNN in the smartphone to refine the result. Furthermore, a crowd-sourcing approach is utilized to update and supplement the positioning database. We perform several experiments comparing our approach with other positioning algorithms on a common smartphone to evaluate the performance of the proposed sensor-calibrated algorithm, and the results demonstrate that the proposed algorithm could significantly improve accuracy, stability, and applicability of positioning.
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China. weichen@nudt.edu.cn.
authors.forename: Wei
authors.initials: W
authors.lastname: Chen
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China. wangwp@nudt.edu.cn.
authors.forename: Weiping
authors.initials: W
authors.lastname: Wang
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China. liqunnudt@163.com.
authors.forename: Qun
authors.initials: Q
authors.lastname: Li
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China. qchang@telin.ugent.be.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Chang
authors.affiliation: College of Information Systems and Management, National University of Defense Technology, Changsha 410073, China. houhongtao@nudt.edu.cn.
authors.forename: Hongtao
authors.initials: H
authors.lastname: Hou
keywords: crowd-sourcing; fingerprint localization; image processing; optical camera; orientation sensor; smartphone