Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Pedestrian navigation on an iPhone today does not provide the accuracy
to place the pedestrian on the correct side of a street. A deciding issue
that prevents sufficient accuracy is the errors that occur when using
satellite positioning in urban environments. Another big problem is
that heading data has shown a tendency to be inaccurate.
Chapter 2 explains satellites navigation, navigation techniques, and
sensors. Chapter 4 describes how a prototype was developed. The prototype
uses deduced reckoning and turn detection to navigate a pedestrian
road network, without relying on satellite signals. The prototype is intended
to run on iPhone 5 and utilizes accelerometer, magnetometer
(compass), and gyroscope data together with detailed data about the
pedestrian network to accurately track a pedestrian. It features a turn
detection method that makes it possible to perform a logical traversal
of the road network, together with step detection and step length estimation
to move around.
The turn detection method was very effective and gave good results
when combined with logical traversal. For the two routes that were
tested the total error in distance estimation was about 3~7 % and for
both routes a close fit to the actual routes was achieved. For individual
parts of the routes the largest distance estimation errors varied between
3 and 15 %.
2013. , 47 p.