Keynote: Validation of the Unfaulted Error Bounds for ARAIM

Todd Walter, Kazuma Gunning, and Juan Blanch

Peer Reviewed

Abstract: Advanced Receiver Autonomous Integrity Monitoring (ARAIM) requires accurate modeling of the unfaulted satellite Signal-In-Space (SIS) error distributions in order to properly calculate integrity risk. This error distribution is most commonly described by two terms: the nominal bias, bnom, and the User Range Accuracy, URA. The nominal, or unfaulted, bias describes unchanging errors such as those due to nominal signal deformation or satellite antenna bias. These error sources are expected to remain the same for the user each time they observe the satellite in a similar manner. Fortunately, they are also expected to be small (sub-meter) compared to other error sources. The broadcast URA is treated as a 1-sigma parameter (which we will denote ?URA) and is used to describe the constantly changing error due mainly to inaccuracies in the broadcast satellite clock and ephemeris parameters. These numbers are set to create upper bounds on the true instantaneous values. Thus, a bounding Gaussian distribution is described where negative errors are no more likely to occur than predicted by N(-bnom, ?URA 2 ) and positive errors are no more likely to occur than predicted by N(bnom, ?URA 2 ). This paper examines how to evaluate the observed instantaneous SIS errors and determine suitable values for bnom and validate the broadcast ?URA. We compare performance against the commitments and broadcast values from the satellites to determine whether the provided values are sufficient or not. An important aspect is to characterize the errors in light of known or predictable characteristics. Oftentimes errors are grouped together to create a single averaged distribution. However, there may be times and conditions where performance is notably worse. We need to separate out such conditions and evaluate the distributions individually so as not to form overly optimistic estimates of the error bounds. Once the representative data sets have been selected, we need to estimate the appropriate bounding parameters. Further we must ensure that these parameters will continue to bound future fault-free behavior. We will describe the conservative steps taken in the estimation process and the validation effort, both with the real data and versus the stated commitments from the constellation service providers.
Published in: Proceedings of the ION 2017 Pacific PNT Meeting
May 1 - 4, 2017
Marriott Waikiki Beach Resort & Spa
Honolulu, Hawaii
Pages: 1 - 19
Cite this article: Walter, Todd, Gunning, Kazuma, Blanch, Juan, "Keynote: Validation of the Unfaulted Error Bounds for ARAIM," Proceedings of the ION 2017 Pacific PNT Meeting, Honolulu, Hawaii, May 2017, pp. 1-19.
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