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Proceedings 2017, 1(8), 786;

Integration and Synchronization of Different Sensors for the Positioning of Moving Vehicles

Centre for Geodesy and Applied Informatics, University of Applied Sciences Stuttgart, 70174 Stuttgart, Germany
Presented at the 5th International Symposium on Sensor Science (I3S 2017), Barcelona, Spain, 27–29 September 2017.
Published: 6 December 2017
(This article belongs to the Proceedings of the 5th International Symposium on Sensor Science (I3S 2017))
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For intelligent mobility concepts in growing urban environments, positioning of cars and generally moving objects is a fundamental prerequisite. Global Navigation Satellite Systems (GNSS) are commonly used for this purpose, but especially in urban environments under certain conditions they offer limited accuracy due to buildings, tunnels etc., that can deviate or mask the satellite signals. The installation of other motion sensors inside the vehicle can be used to describe the movement of the cars independently of GNSS. This conforms to the concept of Dead Reckoning (DR). Both systems (GNSS and DR) can be integrated and prepared to work together since they complement their respective weaknesses efficiently. In this presentation, a method to integrate different sensors (gyroscope, altimeter, accelerometer and wheel-ticks) and GNSS is developed. Extended Kalman Filter (EKF) is the base of calculations to perform data integration. Several driving tests are realized to check the performance of the models. The results show that the developed system is able to improve GNSS positions and even fully substitute this system, e.g., in tunnels, where no GNSS signal is available, as long as this situation is not prolonged too much in time.
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Rawiel, P. Integration and Synchronization of Different Sensors for the Positioning of Moving Vehicles. Proceedings 2017, 1, 786.

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