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Evaluation of Empirical Tropospheric Models Using Satellite-Tracking Tropospheric Wet Delays with Water Vapor Radiometer at Tongji China

机译:卫星跟踪对流层湿延迟和水汽辐射计在对流层经验模型中的应用

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摘要

An empirical tropospheric delay model, together with a mapping function, is commonly used to correct the tropospheric errors in global navigation satellite system (GNSS) processing. As is well-known, the accuracy of tropospheric delay models relies mainly on the correction efficiency for tropospheric wet delays. In this paper, we evaluate the accuracy of three tropospheric delay models, together with five mapping functions in wet delays calculation. The evaluations are conducted by comparing their slant wet delays with those measured by water vapor radiometer based on its satellite-tracking function (collected data with large liquid water path is removed). For all 15 combinations of three tropospheric models and five mapping functions, their accuracies as a function of elevation are statistically analyzed by using nine-day data in two scenarios, with and without meteorological data. The results show that (1) no matter with or without meteorological data, there is no practical difference between mapping functions, i.e., Chao, Ifadis, Vienna Mapping Function 1 (VMF1), Niell Mapping Function (NMF), and MTT Mapping Function (MTT); (2) without meteorological data, the UNB3 is much better than Saastamoinen and Hopfield models, while the Saastamoinen model performed slightly better than the Hopfield model; (3) with meteorological data, the accuracies of all three tropospheric delay models are improved to be comparable, especially for lower elevations. In addition, the kinematic precise point positioning where no parameter is set up for tropospheric delay modification is conducted to further evaluate the performance of tropospheric delay models in positioning accuracy. It is shown that the UNB3 model is best and can achieve about 10 cm accuracy for the N and E coordinate component while 20 cm accuracy for the U coordinate component no matter the meteorological data is available or not. This accuracy can be obtained by the Saastamoinen model only when meteorological data is available, and degraded to 46 cm for the U component if the meteorological data is not available.
机译:对流层经验延迟模型与映射函数一起,通常用于校正全球导航卫星系统(GNSS)处理中的对流层误差。众所周知,对流层延迟模型的准确性主要取决于对流层湿延迟的校正效率。在本文中,我们评估了三个对流层延迟模型的准确性,以及五个在湿延迟计算中的映射函数。通过将它们的倾斜湿延迟与水蒸气辐射计基于其卫星跟踪功能的湿延迟进行比较,从而进行评估(删除了具有较大液态水路径的收集数据)。对于三个对流层模型和五个制图函数的所有15种组合,通过在两种情况下(有气象数据和无气象数据)使用九天数据对它们的精度作为仰角的函数进行统计分析。结果表明:(1)无论有无气象数据,Chao,Ifadis,Vienna Mapping Function 1(VMF1),Niell Mapping Function(NMF)和MTT Mapping Function( MTT); (2)没有气象数据,UNB3比Saastamoinen和Hopfield模型要好得多,而Saastamoinen模型的性能要比Hopfield模型好一些; (3)借助气象数据,对流层三个延迟模型的精度都得到了改进,具有可比性,尤其是在低海拔地区。另外,进行了运动参数的精确点定位,其中没有设置对流层延迟修改的参数,以进一步评估对流层延迟模型在定位精度方面的性能。结果表明,无论是否有气象数据,UNB3模型都是最好的,其N和E坐标分量的精度约为10 cm,而U坐标分量的精度为20 cm。只有当气象数据可用时,才能通过Saastamoinen模型获得此精度;如果没有气象数据,则U分量的精度将降低到46 cm。

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