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Smartphone Positioning in Multi-Floor Environments Without Calibration or Added Infrastructure

Burgess, Simon LU ; Åström, Karl LU orcid ; Högström, Mikael ; Lindquist, Björn and Ljungberg, Rasmus (2016)
Abstract
Indoor positioning for smartphone users
has received a lot of attention in recent years. While
many solutions have been developed, most rely on a
need for pre-deployment of infrastructure or collecting
ground truth data to train on. In this paper we see what
can be done using existing WiFi-infrastructure and
Received Signal Strength from these to smartphones,
not using any calibration of the signal environment or
manually set WiFi positions. We expand on previous
work by using a multi-floor model taking into ac-
count dampening between floors, and optimize a target
function consisting of least squares residuals, to find
positions for WiFis and the smartphone measurement
locations... (More)
Indoor positioning for smartphone users
has received a lot of attention in recent years. While
many solutions have been developed, most rely on a
need for pre-deployment of infrastructure or collecting
ground truth data to train on. In this paper we see what
can be done using existing WiFi-infrastructure and
Received Signal Strength from these to smartphones,
not using any calibration of the signal environment or
manually set WiFi positions. We expand on previous
work by using a multi-floor model taking into ac-
count dampening between floors, and optimize a target
function consisting of least squares residuals, to find
positions for WiFis and the smartphone measurement
locations simultaneously. Pressure sensors are used to
do floor estimation. The method was tested inside two
multi-story buildings, with 5 stories each, with median
errors of smartphone positions of 12.5m and 16.4m and
with WiFi median position errors of 7.16m and 19.4m
respectively. Correct floor detection was achieved for
96% of all smartphone positions. (Less)
Please use this url to cite or link to this publication:
author
; ; ; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)
article number
7743653
pages
8 pages
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:85004168791
ISBN
978-1-5090-2425-4
DOI
10.1109/IPIN.2016.7743653
project
Semantic Mapping and Visual Navigation for Smart Robots
language
English
LU publication?
yes
id
54a28c03-d39e-4836-a4aa-451d8626c5d6
date added to LUP
2016-10-29 15:18:50
date last changed
2022-01-30 07:07:03
@inproceedings{54a28c03-d39e-4836-a4aa-451d8626c5d6,
  abstract     = {{Indoor positioning for smartphone users<br/>has received a lot of attention in recent years. While<br/>many solutions have been developed, most rely on a<br/>need for pre-deployment of infrastructure or collecting<br/>ground truth data to train on. In this paper we see what<br/>can be done using existing WiFi-infrastructure and<br/>Received Signal Strength from these to smartphones,<br/>not using any calibration of the signal environment or<br/>manually set WiFi positions. We expand on previous<br/>work by using a multi-floor model taking into ac-<br/>count dampening between floors, and optimize a target<br/>function consisting of least squares residuals, to find<br/>positions for WiFis and the smartphone measurement<br/>locations simultaneously. Pressure sensors are used to<br/>do floor estimation. The method was tested inside two<br/>multi-story buildings, with 5 stories each, with median<br/>errors of smartphone positions of 12.5m and 16.4m and<br/>with WiFi median position errors of 7.16m and 19.4m<br/>respectively. Correct floor detection was achieved for<br/>96% of all smartphone positions.}},
  author       = {{Burgess, Simon and Åström, Karl and Högström, Mikael and Lindquist, Björn and Ljungberg, Rasmus}},
  booktitle    = {{2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN)}},
  isbn         = {{978-1-5090-2425-4}},
  language     = {{eng}},
  month        = {{10}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Smartphone Positioning in Multi-Floor Environments Without Calibration or Added Infrastructure}},
  url          = {{http://dx.doi.org/10.1109/IPIN.2016.7743653}},
  doi          = {{10.1109/IPIN.2016.7743653}},
  year         = {{2016}},
}