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A Difference Test Method for Early Detection of Slowly Growing Errors in GNSS Positioning

机译:早期检测GNSS定位中缓慢增长的误差的差异测试方法

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摘要

Satellite based navigation system integrity monitoring is essential both for liability and safety critical services. The threats to system integrity are the potential failure modes that could occur at system, operational and user sensor levels. Research on identification, characterisation and modelling of such failure modes, suggests that failures that grow slowly over time (e.g. ramp error less than 2 m/s), also referred to as slowly growing errors (SGE) are the most difficult to detect early. Conventional snapshot algorithms detect SGEs when the test statistic crosses the threshold usually after relatively long periods of time. A recent concept based on the average of residuals over time has been found to have a significant weakness. This paper proposes a "difference test" algorithm capable of detecting SGEs early. In this method, the test statistic is the difference between the norm of current residuals and the norm of the residuals at a previous epoch. The distribution of the test statistic is over-bounded by a normal distribution whose parameters are derived from two Chi-distributions. Results show that the new algorithm results in a significant reduction in detection time compared to conventional methods.
机译:基于卫星的导航系统完整性监控对于责任和关键安全服务都是必不可少的。对系统完整性的威胁是在系统,操作和用户传感器级别可能发生的潜在故障模式。对此类故障模式进行识别,表征和建模的研究表明,随着时间推移缓慢增长的故障(例如,坡道误差小于2 m / s),也称为缓慢增长的误差(SGE),是最难于早期发现的故障。当测试统计量通常在相对较长的时间后超过阈值时,常规快照算法会检测SGE。已经发现基于随时间的平均残差的最新概念具有明显的弱点。本文提出了一种能够及早发现SGE的“差异测试”算法。在这种方法中,检验统计量是当前残差范数与前一个时期的残差范数之间的差。检验统计量的分布被一个正态分布所覆盖,该正态分布的参数来自两个Chi分布。结果表明,与传统方法相比,新算法可显着减少检测时间。

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