Paired overbounding and application to GPS augmentation

Paired overbounding and application to GPS augmentation
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DOI:
10.1109/plans.2004.1309027
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发表时间:
2004-04
期刊:
PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556)
影响因子:
--
通讯作者:
Jason Rife;S. Pullen;B. Pervan;P. Enge
Jason Rife;S. Pullen;B. Pervan;P. Enge
中科院分区:
其他
文献类型:
--
作者:
Jason Rife;S. Pullen;B. Pervan;P. Enge

文献摘要

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距离域误差和位置域误差之间的关系对于GPS增强计划(例如联邦航空管理局的局域增强系统(LAAS))来说仍然是一个公开的问题。本文介绍了一个定理,保证保守的误差界(上界)在位置域给出类似的保守上界广播伪距统计。这个成对的超限定理要求构造一个累积分布函数(CDF)来约束距离域误差分布的两侧。配对超限定理适用于任意误差分布,即使是非零均值、非对称或多峰的误差分布。文中还讨论了成对上界定理在GPS增强中的两个应用。首先,该定理被用来构建一个非零均值高斯分布的膨胀因子;在模拟美国和欧洲10个地点的最坏情况卫星几何形状的背景下,广播西格玛所需的膨胀因子仅为1.18,即使每个卫星的偏差大到10厘米。其次,该定理被应用于约束一个双峰多路径模型紧密,结果剃掉了40%以上的先前建立的通货膨胀因子通过一个更过于保守的分析。
The relationship between range-domain and position-domain errors remains an open issue for GPS augmentation programs, such as the Federal Aviation Administration's Local Area Augmentation System (LAAS). This paper introduces a theorem that guarantees a conservative error bound (overbound) in the position domain given similarly conservative overbounds for broadcast pseudorange statistics. This paired overbound theorem requires that a cumulative distribution function (CDF) be constructed to bound both sides of the range-domain error distribution. The paired overbound theorem holds for arbitrary error distributions, even those that are non-zero mean, asymmetric or multimodal. Two applications of the paired overbound theorem to GPS augmentation are also discussed. First, the theorem is employed to construct an inflation factor for a non-zero mean Gaussian distribution; in the context of a simulation of worst-case satellite geometries for 10 locations in the United States and Europe, the required inflation factor for broadcast sigma is only 1.18, even for biases as large as 10 cm for each satellite. Second, the theorem is applied to bound a bimodal multipath model tightly; the result shaves more than 40% off the previously established inflation factor derived through a more overly conservative analysis.