Improving the Stochastic Model of GNSS Observations by Means of SNR-based Weighting
Improving the Stochastic Model of GNSS Observations by Means of SNR-based Weighting
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DOI：
10.1007/978-3-540-85426-5_83
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发表时间：
2009
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影响因子：
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通讯作者：
Xiaoguang Luo;M. Mayer;B. Heck
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文献类型：
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作者：
Xiaoguang Luo;M. Mayer;B. Heck
在许多GNSS软件包中，都使用了一种简化的观测权重模型，该模型仅基于卫星仰角，并且在方位向对称的假设下有效。基于信号质量与卫星仰角之间存在很强的相关性，这种高度相关加权模型只适用于未受干扰的GNSS信号。然而，对于高精度的大地测量应用，如果观测受到多路径效应、信号绕射以及非理想观测条件下的接收器特性的强烈影响，这种与几何有关的加权模型将变得过时。提出了一种基于信噪比测量的改进观测加权模型，并在Bernese GPS软件5.0中进行了实验实现。试验表明，当该加权模型用于低海拔数据时，可以解决额外10%的模糊问题，并且与标准的随海拔变化的加权模型相比，估计的特定地点的中性层参数的精度可以提高近25%。
In many GNSS software packages a simplified observation weighting model is used which is merely based on the satellite elevation angle and valid under the assumption of azimuthal symmetry. This elevation-dependent weighting model is only suitable for undisturbed GNSS signals based on the existing strong correlation between signal quality and satellite elevation angle. However, for high-precision geodetic applications this geometry-related weighting model becomes obsolete if observations are strongly affected by multipath effects, signal diffraction as well as receiver characteristic under non-ideal observation conditions. An improved observation weighting model based on signal-to noise power ratio measurements has been developed and experimentally implemented in the Bernese GPS software 5.0. Tests indicate that when this weighting model is used for low elevation data additional 10% ambiguities can be resolved and the accuracy of the estimated site-specific neutrosphere parameters can be improved by nearly 25% compared with the standard elevation-dependent weighting model