Baseline advanced RAIM user algorithm and possible improvements

Blanch, Juan; Walker, T M; Enge, Per; Lee, Young; Pervan, Boris; Rippl, Markus; Spletter, Alex; Kropp, Victoria

doi:10.1109/taes.2014.130739

Cited by 190 publications

(254 citation statements)

References 11 publications

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“…When A (i) corresponds to the addition of independent biases to a set of satellites, the least squares solution immune to the fault mode is the least squares solution that excludes the satellites affected by the fault mode (as defined for example in [11]). …”

Section: Case Of One Multi-dimensional Threatmentioning

confidence: 99%

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Theoretical Results on the Optimal Detection Statistics for Autonomous Integrity Monitoring

2017

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One of the most commonly used detection statistics in autonomous integrity monitoring is the solution separation statistic. In this paper, we show that the solution separation statistic is closely linked to the optimal detection statistics. More precisely, we show that in the case of one threat, even multi-dimensional, the optimal detection statistic is the solution separation, and that in the case of many one-dimensional threats, the optimal statistics can be expressed as a function of the solution separations corresponding to each threat. This is achieved by casting the search of the optimal detection region as a mini-max problem and by using the Neyman-Pearson lemma to limit the search of the detection regions to a class of regions parameterized by a bias. These results allow us to establish a lower bound on the minimum achievable integrity risk.

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Section: Case Of One Multi-dimensional Threatmentioning

confidence: 99%

“…The use of solution separation statistics for RAIM was introduced early on [1,7,8] and has been shown to be particularly adapted to Advanced RAIM, where the faults are more complex than in RAIM [9][10][11][12][13][14]. It turns out that in addition, the solution separation statistics have optimal properties in several cases.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Results on the Optimal Detection Statistics for Autonomous Integrity Monitoring

2017

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“…The calculation for VPL is described in reference [17]. The formula for the impact of B nom shows as follows:…”

Section: Araim User Receiver Performancementioning

confidence: 99%

Analysis of BDS ARAIM user receiver nominal bias

Zhang

Wang

Zhu

et al. 2016

2016 Integrated Communications Navigation and Surveillance (ICNS)

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Beidou navigation satellite system (BDS) has provided open services for the most part of the Asia-Pacific region and plans to provide global service in 2020. In the future, it is necessary for BDS to support ARAIM. As an important parameter of ARAIM, the maximum nominal bias (B nom ) of BDS need to be determined. This paper aims to estimate the impact of nominal biases on ARAIM user performance of BDS. In particular, we focus on the signal deformation and the satellite group delay of BDS signal.To estimate the nominal bias caused by the signal deformation, it is assumed that the code measurements are affected by the correlation loss. The ICAO has described the fault signal distortions of broadcast signal. But it is not appropriate to BDS. We chose a model modified by the comprehensive consideration of the filter provided by Stanford University and 2OS TMB configuration provided by Beijing Satellite Navigation Center.Ideally, the satellite antenna is supposed as a point source for the signals. But the real antenna has biases with the look angle. To estimate the nominal bias caused by the satellite group delay, we assume that BDS signal group delay is similar to GPS IIR-A.In order to guarantee the rationality of B nom , a simulation of maximum nominal bias for GPS+BDS has been operated in this paper.

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“…Step 1: Among the fault modes that are going to be monitored (as determined in [7,8]), and for which the a priori probability is above the integrity budget PHMI VERT , select the one with the largest σ (k) 3 . We designate the corresponding coefficients by s max .…”

Section: Suboptimal Approachmentioning

confidence: 99%

“…We will first give an overview of ARAIM and a summary of the user algorithm, which is based on solution separation [3,7,8]. Then, we will show how to decrease the PLs by adjusting the all-in-view position while staying within the same framework.…”

Section: Introductionmentioning

confidence: 99%

A simple position estimator that improves advanced RAIM performance

Blanch

Walter

Enge

et al. 2015

IEEE Trans. Aerosp. Electron. Syst.

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RAIM) that improves availability upon the commonly used least squares estimator. The idea consists in searching the estimator among all affine combinations of the all-in-view least squares estimator and a fault-tolerant estimator-the one corresponding to the most difficult fault to mitigate. Availability simulations show a significant improvement in vertical guidance coverage levels for a dual constellation scenario.

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Baseline advanced RAIM user algorithm and possible improvements

Cited by 190 publications

References 11 publications

Theoretical Results on the Optimal Detection Statistics for Autonomous Integrity Monitoring

Theoretical Results on the Optimal Detection Statistics for Autonomous Integrity Monitoring

Analysis of BDS ARAIM user receiver nominal bias

A simple position estimator that improves advanced RAIM performance

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