Availability prediction method for EGNOS
Availability prediction method for EGNOS
复制标题
EGNOS的可用性预测方法
DOI：
10.1007/s10291-016-0582-5
复制
发表时间：
2017-07
期刊：
影响因子：
4.9
通讯作者：
Yanbo Zhu
中科院分区：
文献类型：
--
作者：
Wei Zhi;Zhipeng Wang;Yanbo Zhu
随着近年来广域差分技术的发展，星基增强系统（SBASs）在许多领域得到了应用。然而，用于产生误差校正的监测站的能力可能会随着地面设备的老化而退化，并且测距和完整性监测站（RIMS）与卫星之间的不良几何结构可能会影响导航系统提供安全生活服务的可靠性。因此，有必要预测SBAS的可用性，以便用户选择安全高效的导航系统。用户差距误差指标（UDREI）和栅格电离层垂直误差指标（GIVEI）的预测是SBAS可用性预测的两个难点。考虑到几何形状对UDREI的影响，定义卫星几何精度稀释系数，区分不同几何形状，从而得到不同几何形状下可见环数与UDREI的关系。针对几何形状对GIVEI的影响，定义了电离层可见穿透点（IPP）的加权数来描述电离层可见穿透点的几何分布，从而得到不同几何形状下电离层可见穿透点数与GIVEI的关系。最后，通过实验验证了所提方法的有效性。使用该预测算法，整个欧洲地区超过75.17%的预测与实际性能一致。特别是在中欧地区，rim的分布较为均匀，一致性水平可以达到95-100%。可以得出结论，该算法的预测性能是令人鼓舞的，该模型可以被认为是预测SBAS可用性的一个很好的竞争者。
Following the recent development of wide-area differential technology, satellite-based augmentation systems (SBASs) have been applied in many fields. However, the capability of monitoring stations used for generating error correction might degenerate with the aging of ground equipment over time, and the poor geometry between ranging and integrity monitoring stations (RIMS) and satellites could affect the reliability of navigation systems in supplying safety of life service. Therefore, it is necessary to predict SBAS availability so that users can choose a safe and efficient navigation system. Predictions of user difference range error indicator (UDREI) and grid ionospheric vertical error indicator (GIVEI) are the two difficulties in predicting SBAS availability. Considering the effect of geometry on UDREI, satellite geometric dilution of precision is defined to distinguish different geometries such that the relationship between the number of visible RIMS and UDREI in different geometries can be obtained. With regard to the effect of geometry on GIVEI, a weighted number of visible ionospheric pierce points (IPPs) is defined to describe the geometric IPP distribution such that the relationship between the number of visible IPPs and GIVEI in different geometries can be achieved. Finally, experiments are performed to evaluate the effectiveness of our proposed method. With the prediction algorithm, the prediction is consistent with actual performance over 75.17% of the entire European region. In particular, when focusing on central Europe, where the distribution of RIMS is uniform, the level of consistency can reach 95–100%. It can be concluded that the prediction performance of the algorithm is encouraging and that this model may be considered a good contender for predicting SBAS availability.
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DOI：
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发表时间：
2000-06
期刊：
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影响因子：
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发表时间：
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期刊：
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影响因子：
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DOI：
10.1007/978-3-319-26109-6_24
发表时间：
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期刊：
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影响因子：
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作者：
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