Title: Exploring Probabilistic Graphical Models in a GNSS Software Receiver
Author(s): Xin Zhang and Xingqun Zhan
Published in: Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017)
September 25 - 29, 2017
Oregon Convention Center
Portland, Oregon
Pages: 3593 - 3598
Cite this article: Zhang, Xin, Zhan, Xingqun, "Exploring Probabilistic Graphical Models in a GNSS Software Receiver," Proceedings of the 30th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2017), Portland, Oregon, September 2017, pp. 3593-3598.
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Abstract: A probabilistic graphical approach to the interpretation of the parameter and state estimation problems in a GNSS software receiver is proposed. This approach turns out to be universal since it can accommodate either a traditional software receiver with scalar tracking loop (STL) or one with a vector tracking loop (VTL). It even has the potential of being easily extended to a multi-sensor integration setting, which can be seen as an alternative solution to the general problems of All Source Positioning and Navigation (ASPN).