Determination of Fault Probabilities for ARAIM

Walter, Todd; Blanch, Juan; Gunning, Kazuma; Joerger, Mathieu; Pervan, Boris

doi:10.1109/taes.2019.2909727

Cited by 33 publications

(25 citation statements)

References 8 publications

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“…These data allow us to obtain accurate estimates of the instantaneous orbit and clock errors for each satellite every fifteen minutes. We can use such data to identify faulted broadcast ephemerides . In this paper, we are examining the nominal or unfaulted error behavior.…”

Section: Gps Datamentioning

confidence: 99%

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Validation of the Unfaulted Error Bounds for ARAIM

et al. 2018

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This paper examines how to evaluate observed instantaneous signal-in-space errors and determine suitable upper bounds on their likely distribution. We compare this 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. 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.

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Section: Gps Datamentioning

confidence: 99%

“…This paper examines the nominal SIS error characteristics. A previous paper examined anomalous behavior and how to determine fault rates. This paper examines how to describe the unfaulted nominal behavior.…”

Section: Introductionmentioning

confidence: 99%

Validation of the Unfaulted Error Bounds for ARAIM

et al. 2018

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“…Constellation performance monitoring and SISRE characterization has been a profuse topic in the GNSS literature during the past years. In particular, in the frame of GNSS SoL applications, previous work done by Walter in previous studies has addressed the analysis of GPS satellites nominal performance and faults during the last decade. In parallel, we have also been active in the examination of GPS and Galileo nominal range error in previous studies .…”

Section: Gps and Galileo Sisre Analysis: Previous Workmentioning

confidence: 99%

“…A discussion regarding whether or not satellite range error distributions are biased is herein addressed. The final section in the Working Group C (WGC) Milestone 3 Report collects a series of assertions related to the ARAIM system architecture. Among others, they state that the ANSP will implement a ground‐based offline monitoring of satellite measurements to compute a safe overbound using the distributions

scriptN false(- b_{n o m}, σ_{ob} false)

and

scriptN false(b_{n o m}, σ_{ob} false)

.…”

Section: Empirical Assertions About Range Error Time Dependencementioning

confidence: 99%

Impact of sample correlation on SISRE overbound for ARAIM

2020

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This paper analyzes the effect of error correlation on the SISRE bounding for GPS and Galileo satellites. For a given period of data collection, it computes the effective number of independent samples contained in a dataset applying an estimation variance analyses. Results show that the time between effective independent samples is highly dependent on the constellation and onboard clock type. On one hand, GPS satellites equipped with Rubidium clocks exhibit significantly longer error correlation than those with onboard Cesium clocks. On the other hand, Galileo satellites show substantially shorter correlation time among samples with less variability on a monthly basis. This paper also introduces a methodology to compute SISRE bounding accounting for the limited number of independent samples. Using a Bayesian approach, it computes the so‐called uncertainty factor by which the Gaussian distribution needs to be inflated in order to account for the observation data independence.

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“…Of particular interest are statistics related to the ARAIM Integrity Support Message (ISM): Psat (probability of satellite fault), Pconst (probability of constellation fault), and the bounding User Range Accuracy (URA) sigmas. Previous studies have characterized nominal performance and estimated Psat and Pconst for GPS [1,2] and GLONASS [3], characterized nominal performance of Galileo [4] and BeiDou [5], or taken a multi-GNSS approach [6]. However, many of these studies are vulnerable to the errors that will be described in this paper.…”

Section: Introductionmentioning

confidence: 99%