Contributions to Books:

A. Ettlinger, H.-B. Neuner, T. Burgess:
"Smartphone Sensor-Based Orientation Determination for Indoor-Navigation";
in: "Progress in Location-Based Services 2016", G. Gartner, H. Huang (ed.); issued by: E120-6; Springer Verlag, 2017, (invited), ISBN: 978-3-319-47289-8, 49 - 68.

English abstract:
Many methods of indoor navigation for smartphones are augmented with
Pedestrian Dead Reckoning (PDR) to improve accuracy and to reduce latency. PDR
requires an accurate estimate of the device orientation. From the pitch and roll
angles the sensor readings can be rotated to the horizontal plane, and with the yaw
angle the direction of movement can be determined. While a simple implementation
using only accelerometer and magnetometer is possible, more accurate results may
be obtained by also including the gyroscope measurements. The approach in this
paper uses a Kalman filter to fuse gyroscope with accelerometer and magnetometer
readings. The system equation uses random walk on straight trajectories and
additional gyroscope readings on turns. Turns are detected using a statistical test on
the innovation of the Kalman filter as well as a condition on the estimated yaw-rate
from the gyroscope. A second Kalman filter separates gravity from specific force by
processing acceleration measurements. The estimated gravity is used in the orientation
filter to determine pitch and roll. The filter has been tested using trajectories
with known ground truth taken with off the shelf mobile devices in corridor and
office environments. The outer heading accuracy approaches 10, dominated by
systematic effects, largely due to magnetic disturbances. The achieved inner
accuracy for the heading is 4.

Indoor-navigation, Orientation determination, Smartphone sensors, Kalman filter, Innovation test

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Created from the Publication Database of the Vienna University of Technology.