Publications in Scientific Journals:

Q. Li, R. Weber:
"Tightly coupled GPS/IMU data integration for the estimation of vehicle trajectories";
European Journal of Navigation, 22 (2022), 1; 32 - 45.

English abstract:
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

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