UAV and autonomous platforms can greatly benefit from an assured position solution with high integrity error bounds. The expected high degree of connectivity in these vehicles will allow users to receive real time precise clock and ephemeris corrections, which enable the use of Precise Point Positioning techniques. Up to now, these techniques have mostly been used to provide high accuracy, rather than focusing on high integrity applications. In this paper we apply the methodology and algorithms used in aviation to determine position error bounds with high integrity (or protection levels) for a PPP position solution.

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In this paper, we provide GNSS multipath error models for automotive applications by leveraging methods used in aviation applications. These error models are intended for navigation integrity and continuity risk evaluation. We provide error models for code and carrier phase GNSS measurements under both static and dynamic multipath environments. The dynamic dataset was collected in realistic driving conditions for a vehicle traveling in an urban canyon and on a highway with overpasses and road signs. The static test was conducted in a more controlled environment, first, to precisely evaluate measurement errors under open sky, and then, to quantify the effect on multipath error of a semi-truck next to a car equipped with a commercial GNSS antenna. In this paper, we characterize the errors by the mean and standard deviation of a bounding Gaussian distribution and by the autocorrelation time constant of the measurement errors.

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