A Method of Over Bounding Ground-Based Augmentation System (GBAS) Heavy Tail Error Distributions

Ronald Braff, Curtis Shively

Abstract:	The purpose of this paper is to describe a statistical method of modeling and accounting for the heavy tail fault-free error distributions that have been encountered in the Local Area Augmentation System (LAAS), the FAA’s version of a ground-based augmentation system (GBAS) for GPS. The method uses the Normal Inverse Gaussian (NIG) family of distributions to describe a heaviest tail distribution, and to select a suitable NIG family member as a model distribution based upon a statistical observability criterion applied to the FAA’s LAAS prototype error data. Since the independent sample size of the data is limited to several thousand and the tail probability of interest is of the order of 10-9, there is a chance of mismodeling. A position domain monitor (PDM) is shown to provide significant mitigation of mismodeling, even for the heaviest tail that could be encountered, if it can meet certain stringent accuracy and threshold requirements. Aside from its application to GBAS, this paper should be of general interest because it describes a different approach to navigation error modeling and introduces the application of the NIG distribution to navigation error analysis.
Published in:	Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004) September 21 - 24, 2004 Long Beach Convention Center Long Beach, CA
Pages:	2797 - 2809
Cite this article:	Braff, Ronald, Shively, Curtis, "A Method of Over Bounding Ground-Based Augmentation System (GBAS) Heavy Tail Error Distributions," Proceedings of the 17th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS 2004), Long Beach, CA, September 2004, pp. 2797-2809.
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