接收机自主完整性监测
计算机科学
全球导航卫星系统应用
全球定位系统
一致性(知识库)
加权
系统完整性
作战空间
实时计算
数据挖掘
可靠性工程
工程类
人工智能
计算机安全
医学
电信
放射科
出处
期刊:Proceedings of the 8th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 1995)
日期:1995-09-15
卷期号:: 1995-2004
被引量:191
摘要
The use of differential GPS is becoming
increasingly popular for real-time navigation systems. As
these systems migrate to safety-of-life applications (e.g.
precision approach and landing), their integrity becomes
more important than their accuracy. One method for
increasing both accuracy and integrity is the use of
weighting in the navigation solution. This method uses a
priori information to weight certain satellites (e.g. those
at higher elevation) over other satellites. The accuracy
increases because we better use the information available.
The integrity increases because satellites that are more
likely to introduce error contribute less to the solution.
A weighted position solution by itself does not
provide sufficient integrity to support precision approach.
However, this method can be combined with a weighted
form of Receiver Autonomous Integrity Monitoring
(RAIM) to increase the level of integrity. RAIM uses
redundant measurements to check the consistency of an
overdetermined solution. This check is crucial because
only a user can detect certain error types (e.g. severe
airframe multipath or local interference). A differential
reference station can detect many types of errors.
However, it is only at the user where all the information
is combined. The use of RAIM (or some form of
integrity at the user) must be combined together with
integrity checking at the reference station to provide the
overall safety of the system.
Weighted RAIM is investigated for application to
Category I precision approach as supported by a Wide
Area Augmentation System (WAAS). This paper details
how to implement weighted RAIM and how to use
geometry selection to guarantee a certain level of
protection. Also, we provide information on the
availability of these geometries. The results are based
upon analysis, Monte Carlo simulation and actual data
collected from Stanford University’s wide-area differential
GPS network.
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