摘要
针对北斗/GPS短基线相对定位中北斗中轨道卫星多路径重复周期过长的问题,提出了引进随机游走估计方法,并建立了北斗/GPS多路径随机游走模型。实验选取了句容抽水蓄能电站大坝在不同观测环境下的观测数据进行动态差分定位,验证了该方法改正北斗卫星多路径误差、提高形变监测结果精度和可靠性的能力。结果表明,使用前一天的北斗卫星数据获得的北斗多路径随机游走模型的方差因子精度较高,可以达到应用需求。此外,多路径随机游走估计方法能够有效改正双差观测值中的多路径误差,常规环境下残差减少率最高超过30%,积雪环境下最高超过60%。动态定位结果表明该方法能够显著提高定位精度,且可以有效改正强多路径环境下定位结果存在的偏差,获取高可靠性定位结果。常规环境下,水平方向和高程方向的定位精度分别提高了30.3%和25.2%;积雪环境下,水平方向和高程方向的定位精度分别提高了56.6%和33.5%。
Considering the problem of long multipath repeat cycles of BDS medium earth orbit satellite in BDS/GPS deformation monitoring,this paper introduced the multipath random walk method(RWM)and established a BDS/GPS multipath random walk model.Observation data from the Jurong reservoir dam was tested in real-time kinematic positioning to verify the capability of RWM in correcting the multipath error of BDS satellite and improving the positioning accuracy.The results indicate that the variance factor accuracy of the RWM obtained using the BDS observation data only from the previous day is high and can meet the application requirements.In addition,the RWM can effectively correct the multipath errors in double-difference observations,with a residual reduction rate of over 30%in conventional environments and over 60%in snow-covered environments.The kinematic positioning results show that the RWM method can significantly improve the positioning accuracy.In addition,this method can effectively correct positioning errors in strong multipath environments and obtain highly reliable positioning results.In conventional environments,the positioning accuracy in the horizontal and vertical directions has increased by 30.3%and 25.2%,respectively.In snow-covered environments,the positioning accuracy in the horizontal and vertical directions increased by 56.6%and 33.5%,respectively.
作者
梁睿斌
徐祥
李明
陈昊
何秀凤
詹伟
LIANG Ruibin;XU Xiang;LI Ming;CHEN Hao;HE Xiufeng;ZHAN Wei(Jiangsu Jurong Pumped Storage Company Limited,Jurong 212400,China;School of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China)
出处
《甘肃科学学报》
2025年第5期28-38,共11页
Journal of Gansu Sciences
基金
国网新源集团(控股)有限公司科技项目(SGXYKJ-2022-124)。
