Abstract
This paper presents a User Range Accuracy (URA)/Signal-in-Space Accuracy (SISA) analysis to support ARAIM based on a time-dependent statistical characterization of orbit and clock error observations. By comparing precise orbits to broadcast ephemeris for each individual GPS and Galileo satellite, this work computes the Signal-in-Space Range Error (SISRE) that needs to be overbounded by the URA/SISA value included in the Integrity Support Message (ISM). Service data from January 2008 to February 2015 for GPS and from March to June 2015 for Galileo are processed, showing that range error is mainly driven by satellite's clock performance. In order for the ISM generation to account for the variation in error biases and standard deviation, GPS service history is broken down into monthly, quarterly, and yearly datasets. Results reveal that orbit and clock error distributions are non-zero mean on a monthly basis, although biases tend to reduce as sample set size increases.
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