infranstructure based solutions, such as GPS, are not available. The principle of operation
is based on the ability to accurately measure the velocity vector i.e. both the amplitude
(speed) and direction, starting from a known reference point. An accurate
starting point can be assumed from a standalone positioning technology such as
GPS, and the direction of movement can also be obtained with delity using a
combination of magnetometers and gyroscopes. In order to determine the walking
speed and thus the displacement compared to the reference position, accelerometers
together with statistical models of the human walk are used to detect steps
and to estimate the step length. However, these step-length estimators require
user calibration and fail in practice when the user is moving with an irregular
posture like crawling, sliding on a slippery surface, using the fast walking lane in
an airport, riding a bicycle or skateboarding.
This dissertation proposes a novel speed estimation method for pedestrian
dead-reckoning, which is based on the coherence time of wideband terrestrial wireless
systems. In the proposed method, the coherence time is dened as the time
required for the envelope correlation coecient of a wideband frequency-selective
channel frequency response vector to drop below a certain threshold value.
The eect of the several channel propagation conditions, such as signal-to-noise
ratio, the direction-of-arrival of the line-of-sight component and Rician factor, is
investigated on the performance of the proposed method.
Moreover, a proof-of-concept hardware demonstrator is realized and several
experimental measurement campaigns are conducted to verify the performance of
the proposed algorithm under real-world indoor conditions.
Experimental results indicate that speed estimation errors lead to an average
positioning uncertainty of 1:1% of the total traveled distance with a standard
deviation of 2:4% from the average. Moreover, there is a probability of 97% that
the absolute positioning uncertainty will be less 4.5% of the traveled distance.
It is demonstrated that the proposed speed estimation method outperforms
traditional pedestrian dead-reckoning systems, which are based on step length
estimators. In addition, the proposed algorithm does not require user calibration
and it is not based on a particular type of movement because it solely measures
the absolute speed of the moving antenna.