Cargando…
Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device
Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721787/ https://www.ncbi.nlm.nih.gov/pubmed/26694387 http://dx.doi.org/10.3390/s151229867 |
_version_ | 1782411281137926144 |
---|---|
author | He, Xiang Aloi, Daniel N. Li, Jia |
author_facet | He, Xiang Aloi, Daniel N. Li, Jia |
author_sort | He, Xiang |
collection | PubMed |
description | Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. |
format | Online Article Text |
id | pubmed-4721787 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-47217872016-01-26 Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device He, Xiang Aloi, Daniel N. Li, Jia Sensors (Basel) Article Nowadays, smart mobile devices include more and more sensors on board, such as motion sensors (accelerometer, gyroscope, magnetometer), wireless signal strength indicators (WiFi, Bluetooth, Zigbee), and visual sensors (LiDAR, camera). People have developed various indoor positioning techniques based on these sensors. In this paper, the probabilistic fusion of multiple sensors is investigated in a hidden Markov model (HMM) framework for mobile-device user-positioning. We propose a graph structure to store the model constructed by multiple sensors during the offline training phase, and a multimodal particle filter to seamlessly fuse the information during the online tracking phase. Based on our algorithm, we develop an indoor positioning system on the iOS platform. The experiments carried out in a typical indoor environment have shown promising results for our proposed algorithm and system design. MDPI 2015-12-14 /pmc/articles/PMC4721787/ /pubmed/26694387 http://dx.doi.org/10.3390/s151229867 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons by Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article He, Xiang Aloi, Daniel N. Li, Jia Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title | Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title_full | Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title_fullStr | Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title_full_unstemmed | Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title_short | Probabilistic Multi-Sensor Fusion Based Indoor Positioning System on a Mobile Device |
title_sort | probabilistic multi-sensor fusion based indoor positioning system on a mobile device |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4721787/ https://www.ncbi.nlm.nih.gov/pubmed/26694387 http://dx.doi.org/10.3390/s151229867 |
work_keys_str_mv | AT hexiang probabilisticmultisensorfusionbasedindoorpositioningsystemonamobiledevice AT aloidanieln probabilisticmultisensorfusionbasedindoorpositioningsystemonamobiledevice AT lijia probabilisticmultisensorfusionbasedindoorpositioningsystemonamobiledevice |