eprintid: 2796
rev_number: 8
eprint_status: archive
userid: 328
dir: disk0/00/00/27/96
datestamp: 2017-12-26 07:00:28
lastmod: 2017-12-26 07:00:28
status_changed: 2017-12-26 07:00:28
type: conference_item
metadata_visibility: show
creators_name: Hoang, Manh Kha
creators_name: Duong, Thi Hang
creators_name: Vu, Trung Kien
creators_name: Trinh, Anh Vu
creators_id: khamh@gmail.com
creators_id: duongthihang.haui@gmail.com
creators_id: kienvt@gmail.com
creators_id: vuta@vnu.edu.vn
title: Enhancing WiFi based Indoor Positioning by Modeling Measurement Data with GMM
ispublished: inpress
subjects: Communications
divisions: fac_fet
abstract: Abstract—Recently, indoor positioning has been investigated by many research groups. Several proposals for indoor positioning have been developed over the last decades, amongst them, WiFi fingerprinting based is considered as the most promissing approach. However, many challenges are still remained for improving the accuracy of indoor mobile object localization. This paper presents a novel approach for enhancement of WiFi fingerprinting based indoor positioning by using Gaussian Mixture Model (GMM) to model the measured Received Signal Strength Index (RSSI) distributions. Since the measured data
varies due to obstacles in indoor environments as well as user directions, the proposed approach is able to model the data distribution more precise than the previous popular approach which utilizes single Gaussian. Simulation results demonstrate the effectiveness of the proposed approach compared to the others.
date: 2017-10-18
date_type: published
official_url: http://atc-conf.org/
full_text_status: none
pres_type: poster
pagerange: 325-328
event_title: International Conference on Advanced Technologies for Communications
event_location: Quy Nhon, Viet Nam
event_dates: 18-20, October, 2017
event_type: conference
refereed: FALSE
citation:   Hoang, Manh Kha and Duong, Thi Hang and Vu, Trung Kien and Trinh, Anh Vu  (2017) Enhancing WiFi based Indoor Positioning by Modeling Measurement Data with GMM.  In: International Conference on Advanced Technologies for Communications, 18-20, October, 2017, Quy Nhon, Viet Nam.    (In Press)