Localization and Monitoring of Vehicles supported by Inertial Sensors
The goal is to develop fundamental nonlinear filtering and estimation methods with applications to speed estimation in wheel based vehicles.
Illustration of a spectrogram (time-varying frequency content) computed from a vehicle mounted accelerometer, compared to the estimated harmonics.
The manufacturing industry always look for opportunities to replace costly and sensitive sensors with cheaper and more robust ones. The wheel speed sensor is one such sensor that is exposed to harsh environment and is a relatively costly part of vehicles. In some applications, a contact-less accelerometer can be used instead.
By analyzing the time-varying spectrum of the vibrations caused by the wheel, the wheel speed can be computed. Another potential application is to support IoT devices where speed information is needed when located on a vehicle. Here, wired solutions to the existing sensors can be excluded. Speed estimation in cellphones is one further application.
This project has developed algorithms tailored to this problem that extend current theory in nonlinear filtering.