Reduced ARAIM monitoring subset method based on satellites in different orbital planes

Abstract

With the development of the Global Navigation Satellite System, the increased number of satellites has resulted in more fault hypothesis situations and subset solutions. This situation represents a new challenge for advanced receiver autonomous integrity monitoring (ARAIM) in terms of the computational load. To efficiently detect faults and reduce the computational load, a method based on the association between satellite features in the same orbital plane is proposed. This approach first tests subsets that exclude entire constellations to narrow the search range for faults. Next, we evaluate multiple-fault cases directly by utilizing the subsets that exclude entire orbit satellites. Compared with the baseline Multiple Hypothesis Solution Separation (MHSS) method, our method can clearly reduce the number of subsets and the computational time under a typical multi-constellation situation while satisfying the localizer precision vertical 200 performance requirement, i.e., the guidance supports approach operations down to 200-foot altitudes. Furthermore, the experimental results illustrate that the number of subsets is reduced at most by two orders of magnitude, from 1330 to 87, and the computational time is decreased by 66.6%. The effective monitoring threshold and the fault-free 10⁻⁷ error bound on the accuracy of our method are much closer to those of the baseline MHSS method, and the usability coverage of both methods reaches 100%. This study verifies that the monitoring subsets and the calculation time for ARAIM are dramatically reduced by the new method.