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首页> 外文期刊>Journal of Aeronautics, Astronautics and Aviation, A >Mitigation of Ionospheric Effect on Multi-GNSS Positioning with Ionosphere Delay Estimation Using Single-Frequency Measurements of Selected Satellites
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Mitigation of Ionospheric Effect on Multi-GNSS Positioning with Ionosphere Delay Estimation Using Single-Frequency Measurements of Selected Satellites

机译：采用选定卫星单频测量对电离层延迟估计对多GNSS定位的电离层效应的减轻

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摘要

Ionosphere delay is the largest source of positioning error for single point positioning using single-frequency receiver of global navigation satellite system (GNSS). To mitigate the effect of ionosphere which varies sometimes rapidly and locally due to the solar activity, we propose estimating the ionosphere delay in the process of positioning calculation by using the ionospheric thin shell model with single-frequency pseudorange measurement of single epoch. Since sufficient number of visible satellites is observable for multi-GNSS positioning, all those measurements are not necessarily used. We propose algorithm of selecting useful satellites by the residual ranging error of pseudorange measurement to mitigate the positioning error. The performance evaluation for proposed selection algorithm and ionosphere delay estimation was conducted by using L1 pseudorange measurements of global positioning system (GPS) and GLONASS on both quiet and disturbed ionospheric conditions. Proposed selection algorithm reduced the rms of horizontal positioning error by about 10% on disturbed condition. Proposed ionosphere delay estimation increased the average of horizontal error reduction by 30% in daytime on disturbed condition, compared with the conventional correction method using Klobuchar model.
机译：电离层延迟是使用全球导航卫星系统（GNSS）的单频接收器单点定位的定位误差最大的定位误差源。为了减轻电离层的作用，其由于太阳能活性有时迅速和局部而变化，我们通过使用具有单频伪距测量的单元薄壳模型来估算定位计算过程中的电离层延迟。由于多GNSS定位可观察到足够数量的可见卫星，因此不必使用所有这些测量。我们通过伪距测量的残余测量误差提出了选择有用卫星来减轻定位误差的算法。通过使用全球定位系统（GPS）的L1伪距测量和GLONASS在安静和受扰动的电离层条件下进行了所提出的选择算法和电离层延迟估计的性能评价。所提出的选择算法将水平定位误差的RMS降低约10％的受干扰条件。与使用Klobuchar模型的常规校正方法相比，所提出的电离层延迟估计在白天时，白天在干扰条件下减少30％的平均值。

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