电离层延迟参数随机建模对GPS非组合精密单点定位的影响分析

提出顾及电离层延迟历元间变化的随机游走模型，利用全球分布的170个IGS测站2016-07观测数据，采用静态和仿动态PPP解算模式，分析3种随机模型对PPP收敛时间和定位精度的影响。结果表明，该随机游走模型在收敛时间上不受随机游走模型谱密度的影响，且在较小谱密度时收敛效果明显优于传统随机游走模型；从定位精度来看，该模型与白噪声模型结果相当，静态模式下平均RMS约为5 cm，动态模式下平均RMS约为8 cm。

Impact of Stochastic Modeling of Ionospheric Delays on GPS Uncombined Precise Point Positioning

A new random walk process considering between-epoch variations of ionospheric delays is employed. GPS data sets collected from 170 globally distributed stations of the International GPS Service(IGS) network in a one-month period(July 2016) are exclusively processed in static and simulated kinematic modes. The convergence time and positioning accuracy are used as indicators to validate the stochastic modeling for ionospheric parameters. For the convergence performance, the proposed model is not affected by the spectral density of the random walk process, while the convergence performance is much better than the traditional random walk process at the small spectral density. Positioning accuracy derived from the proposed model and the white noise process are comparable, with an average RMS of 5 cm in static mode, and 8 cm in kinematic mode.