Enhancements of the Range Consensus Algorithm (RANCO)

Abstract

In anticipation of the future GNSS constellations
\nbecoming operational, it will no longer be possible to
\nassume that the probability of failure for more than one
\nsatellite within a certain timeframe is negligible. Further,
\nit is questionable whether it is always reasonable to
\ncompute a position estimate based on all satellites in
\nview, rather than selecting the “best” subset.
\nThe Range Consensus (RANCO) algorithm is not only
\ncapable of detecting multiple satellite failures at a time,
\nbut it also allows the determination of good estimates of
\nthe current ranging biases. RANCO calculates position
\nsolutions based on subsets of four satellites and compares
\nthis estimate with the pseudoranges of all the satellites not
\ncontributing to this solution. The residuals of this estimate
\nare then used as a measure of statistical consensus.
\nThe scope of this work is the optimization of the
\nperformance of RANCO by restricting it to the detection
\nof a certain number of failed satellites at a time and by
\nfinding an optimal subset selection process for this
\nconstraint. Furthermore, the computation of the subset
\nquality was reconsidered and significantly improved by
\nthe use of the Weighted Dilution of Precision (WDOP).
\nIn this paper, the physical model for determining the
\nthreshold for the separation between correct and faulty
\nsatellite signals has been extended. The RANCO
\nalgorithm was also verified with respect to its capability
\nof detecting and identifying satellites with a bias higher
\nthan a given threshold. Throughout the paper those
\nsatellites are defined to fail.
\nThe abilities of RANCO, to exclude multiple
\nsimultaneous ranging faults and low biases, paves the way
\nfor safety critical applications by combining receiver
\nautonomous algorithms with the integrity channel
\ninformation from future GNSS systems.