Publications in Scientific Journals:
Q. Li, R. Weber:
"Tightly coupled GPS/IMU data integration for the estimation of vehicle trajectories";
European Journal of Navigation,
Over the past years a software package employing the tightly coupled Kalman filter algorithm has been developed at the Department of Geodesy and Geoinformation (TU-Vienna). The software allows for the fusion of GPS and IMU data and accepts also odometer measurements, which enables a reliable vehicle positioning performance in post-processing mode. This approach has been utilized to estimate the trajectories of slow and fast-moving vehicles like cars or trains. A passenger vehicle or a rail vehicle can simply be equipped with a GPS unit, an IMU device, and other navigation sensors. Different GPS processing strategies based on the double-difference approach (DD) with code-only processing and combined code plus carrier phase processing are implemented and investigated. In the presented test cases, an iMAR IMU device and a JAVAD GPS receiver fixed on a private car provide the data input for the filter algorithm. The quality of our solution was assessed against trajectories calculated with the commercial Inertial Explorer software from NovAtel [Novatel]. All sensor data and reference trajectories were generated and provided thankfully by colleagues from the research group Navigation at TU Graz.
Positioning, Kalman filter, Sensor fusion
Created from the Publication Database of the Vienna University of Technology.