Smartphone Positioning in Multi-Floor Environments Without Calibration or Added Infrastructure
Burgess, Simon; Åström, Karl; Högström, Mikael; Lindquist, Björn, et al. (2016-10-07). Smartphone Positioning in Multi-Floor Environments Without Calibration or Added Infrastructure 2016 International Conference on Indoor Positioning and Indoor Navigation (IPIN): IEEE - Institute of Electrical and Electronics Engineers Inc.
Conference Proceeding/Paper
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Published
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English
Authors:
Burgess, Simon
;
Åström, Karl
;
Högström, Mikael
;
Lindquist, Björn
, et al.
Department:
Mathematics (Faculty of Engineering)
Mathematical Imaging Group
ELLIIT: the Linköping-Lund initiative on IT and mobile communication
eSSENCE: The e-Science Collaboration
Project:
Semantic Mapping and Visual Navigation for Smart Robots
Research Group:
Mathematical Imaging Group
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 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.
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