Evaluation of GNSS RF-signal simulators and -receivers based on recorded multi GNSS signals in scenarios of traffic telematics

Global Navigation Satellite Systems (GNSS) such as GPS or GLONASS form a fundamental basis for the optimization of traffic processes over all modes of transport (road, rail, air and water). Reliable location, navigation and timing information of the operating traffic participants serve as a basis for that. In traffic telematics, algorithms to locate and track vehicles, people and objects play an important role. Both the choice of input data in the form of number and type of data to be fused as well as the functioning of algorithms themselves are of decisive importance. Future system concepts, such as fully automated driving, need the compliance of integrity, continuity and especially positioning requirements of the used traffic ways. For example a necessary lane-selective localization of vehicles on the road or a high-precision positioning in inland navigation during a lockage is meant. From operational point of view, field tests for GNSS measurements in rail traffic an d inland navigation are difficult in planning, work-intensive in theirs realization and expensive in theirs implementation. Furthermore validation tests regarding receiver hardware and positioning or tracking algorithms require comparable and repeatable signal conditions. In general, this task represents a challenge for GNSS measurements because satellite geometry, ionospheric conditions and environmental reflections change steadily. A solution for the above problems is the use of a modular GNSS radio frequency (RF) signal simulator for mobile field trials. A RF signal simulator consists of a RF generator unit and a RF recorder unit. On the one hand the generator unit is able to output synthetic protocol-compliant GNSS signals and on the other hand it is able to replay GNSS signals reproducibly, recorded during field tests. Both methods offer advantages and disadvantages. The protocol-compliant generation of synthetically generated GNSS signals offers the advantage of knowledge about noise performan