摘要
参考站网整周模糊度固定是网络RTK高精度实现的基础,但随着参考站间距增加,大气误差的空间残余使得参考站解算困难,特别是时空变化复杂的电离层延迟误差,严重影响参考站网固定的性能。参考站模糊度解算时将大气参数以随机游走的方式进行估计,本文在分析电离层功率谱密度(ionospheric power spectral density,IPSD)对参考站模糊度固定性能的基础上,研究不同差分间隔的电离层观测值的时变特性。通过观测噪声和电离层随差分时间间隔的不同变化趋势,削弱电离层观测值噪声来确定IPSD,优化参考站模糊度估计中电离层参数的随机模型,进而提升长距离参考站网的固定效率,不再采用未考虑大气变化的经验值或经验模型。试验结果表明,通过1 s采样间隔数据实时估计的IPSD可以优化参考站整周模糊度的浮点解精度,同时也能缩小整周模糊度的搜索范围,与电离层经验功率谱密度的参考站模糊度固定性能比较,本文方法在基线长度100 km以上的5个参考站网中收敛时间提升21%,模糊度固定成功率也得到相应提升。
The integer ambiguity resolution of the reference station network is the basis of high precision positioning of network RTK.However,with the increase of the range of the reference stations,the spatial residual of atmospheric error makes it difficult to resolution reference station,especially the ionospheric delay error with complex temporal and spatial variation,which seriously affects the resolution performance of the reference station network.The atmospheric parameters are estimated by random walk when the ambiguity resolution of the reference station.Based on the analysis of the ionospheric power spectral density(IPSD)on the ambiguity resolution performance of the reference station,this paper studies the time-varying characteristics of ionospheric observations with different differential intervals.By observing the different trends of noise and ionosphere with differential time intervals,the ionospheric observation noise is weakened to determine the IPSD,and the stochastic model of ionospheric parameters in the ambiguity estimation is optimized,so as to improve the fixed efficiency of the long-distance reference station network,instead of using empirical values or empirical models that do not consider atmospheric variation.The experimental results show that the IPSD estimated in real-time by the 1 s sampling interval data can optimize float solution accuracy of the integer ambiguity of the reference station,and can also reduce the search space of the integer ambiguity.Compared with empirical ionospheric power spectral density,the method proposed in this paper can improve the convergence time by 21%in five reference station networks with a baseline length of more than 100 km,and the success rate of ambiguity resolution is also improved accordingly.
作者
李军
祝会忠
刘智强
LI Jun;ZHU Huizhong;LIU Zhiqiang(School of Geomatics,Liaoning Technical University,Fuxin 123000,China)
出处
《测绘学报》
北大核心
2025年第2期221-232,共12页
Acta Geodaetica et Cartographica Sinica
基金
国家自然科学基金(42030109
42074012)
辽宁省“兴辽英才计划”项目(XLYC2203162)。
关键词
网络RTK
整周模糊度固定
随机模型
电离层误差
功率谱密度
network RTK
integer ambiguity resolution
stochastic model
ionospheric error
power spectral density
