Cooperative GNSS Signal Processing Algorithms for Intelligent Transport Systems

R. Bauernfeind, D. Dötterböck, E. Gkougkas, B. Eissfeller

Abstract:	Current activities in standardization of cooperative intelligent transport systems (C-ITS) lead the way into a future where vehicles apply information and communication technology to improve transportation efficiency, sustainability and safety. Primary technologies enabling C-ITS are GNSS, by providing location information of vehicles, and vehicular ad-hoc networks (VANETs), which have been introduced in order to enable real-time communication of vehicle position and state. Applications like Intersection Collision Risk Warning and Longitudinal Collision Risk Warning will be based on the technology relying to a great extent on GNSS positioning performance. The advantages of communication of vehicle position based collision risk warning systems over radar systems are extended range, also to non-nearest neighbors and non-line-of-sight capability but with the disadvantage that the applications are dependent on other cooperating vehicles, and the accuracy and integrity of their position solution. Current mass market receivers do not provide sufficient accuracy for collision avoidance applications. In context of the paper possibilities will be explored on how to use the C-ITS infrastructure for cooperative interference and multipath mitigation techniques and cooperative relative positioning based on GNSS raw data exchanges between vehicles. For cooperative interference and multipath mitigation use cases, the Local Dynamic Map (LDM) will be used to develop situation awareness on the GNSS signal environment. The LDM is a central element in the C-ITS infrastructure which is a geographical database, managing all relevant information. For cooperative interference mitigation the relevant interference sources (like DME transmitters) with signal parameters will be stored in the LDM for its use in the interference detection and mitigation algorithm. The implemented interference mitigation algorithm is based on the Short-Time Fourier Transform (STFT). With the STFT the IF sample stream is transformed in the time-frequency domain, where the frequency bins containing the interference are zeroed, followed by an inverse STFT transformation. For cooperative multipath mitigation, the LDM is used to provide relevant information on the multipath environment for the current vehicle position. The entries in the database are generated cooperative based on detection from capable vehicular GNSS receivers and ray tracing of the multipath signals. In order to enhance the accuracy of relative positioning in the vehicular ad-hoc network, techniques based on raw data exchanges between vehicles are investigated. One approach is based on the use of post-correlation I/Q values, which allows a robust and accurate estimate of the vehicle trajectory. For the assessment of the techniques scenarios are defined and simulated with a GNSS constellation simulator. For the analysis of the communication architecture the already existing standards will be considered and requirements for further developments will be derived. The prototyping of the described techniques and algorithms is done with the Institute of Space Technology and Applications PC-based Experimental Software Receiver (ipexSR). The ipexSR is a real-time capable multi frequency, multi constellation software receiver with interface to the LDM database (Postgresql with PostGIS extension).
Published in:	Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013) September 16 - 20, 2013 Nashville Convention Center, Nashville, Tennessee Nashville, TN
Pages:	645 - 655
Cite this article:	Bauernfeind, R., Dötterböck, D., Gkougkas, E., Eissfeller, B., "Cooperative GNSS Signal Processing Algorithms for Intelligent Transport Systems," Proceedings of the 26th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2013), Nashville, TN, September 2013, pp. 645-655.
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