Reducing convergence time of precise point positioning with ionospheric constraints and receiver differential code bias modeling
Reducing convergence time of precise point positioning with ionospheric constraints and receiver differential code bias modeling
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DOI：
10.1007/s00190-019-01334-x
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发表时间：
2020-01
影响因子：
4.4
通讯作者：
Yan Xiang;Yang Gao;Yihe Li
中科院分区：
文献类型：
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作者：
Yan Xiang;Yang Gao;Yihe Li
传统的双频精密单点定位（PPP）方法由于收敛时间长而限制了其广泛应用。与传统的PPP方法不同，非组合PPP方法基于原始观测值估计电离层延迟。当有外部电离层信息时，由于位置与电离层参数之间的相关性降低，可将其作为一种约束条件，以帮助缩短收敛时间。然而，当应用外部电离层信息时，接收机差分码偏（DCB）将是一个问题。对于接收机DCB，通常假设接收机时钟参数可以吸收偏置。我们已经证明，接收机DCB不能被一个接收机码时钟参数完全同化，因为接收机DCB在任何频率下对码和载波相位测量具有不同的影响。额外的参数是必要的，以模拟接收机DCB，使其对定位解决方案的影响可以被最小化。我们开发了一个电离层约束的PPP模型，将电离层总电子含量（TEC）的倾斜（STEC）和垂直（VTEC）时，利用区域网络和全球电离层地图（GIMs）。静态和运动学实验结果表明，该算法能显著提高收敛时间和定位精度。在第一个历元的精度为0.4米的GIM约束，和0.2米的区域约束，是可以实现的。在68%的置信水平下，1 dm水平精度的收敛时间减少到7.5 min。
Long convergence time has limited the wide application of traditional precise point positioning (PPP) based on an ionosphere-free combination of dual-frequency observations. Different from the traditional PPP, the uncombined PPP method based on raw observations estimates ionospheric delays. When external ionospheric information is available, it can be applied as a constraint to help shorten the convergence time, as a result of the reduced correlation between the position and the ionospheric parameters. The receiver differential code biases (DCBs) will be a concern, however, when applying the external ionospheric information. For receiver DCBs, it is usually assumed that the biases can be absorbed by the receiver clock parameters. We have demonstrated that the receiver DCBs cannot be fully assimilated by one receiver code clock parameter because the receiver DCBs have different effects on the code and carrier phase measurements at any frequency. Additional parameters are necessary to model the receiver DCBs so that their effects on the positioning solution can be minimized. We developed an ionosphere-constrained PPP model to incorporate ionospheric total electron content (TEC) in the slant (STEC) and vertical (VTEC) when leveraging a regional network and global ionospheric maps (GIMs). Both static and kinematic experimental results show that the convergence time and the positioning accuracy can be improved significantly. Accuracies at the first epoch of 0.4 m for GIM constraints, and 0.2 m for the regional constraints, are achievable. The convergence time to 1 dm horizontal accuracy is reduced to 7.5 min at a 68% confidence level.