Comparative evaluation and analysis of different tropospheric delay models in Ghana

IF 0.3 Q4 REMOTE SENSING
S. Osah, Akwasi Acheampong, I. Dadzie, C. Fosu
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Abstract

Tropospheric delay prediction models have become increasingly important in Global Navigation Satellite System (GNSS) as they play a critical role in GNSS positioning applications. Due to the different atmospheric conditions over the earth regions, tropospheric effect on GNSS signals also differs, influencing the performance of these prediction models. Thus, the choice of a particular prediction model can significantly degrade the positioning accuracy especially when the model does not suit the user’s environs. Therefore, a performance assessment of existing prediction models in various regions for a suitable one is very imperative. This paper evaluates and analyses seven commonly used tropospheric delay models in Ghana in terms of performances in Zenith Tropospheric Delay (ZTD) estimation and baseline positional accuracies using data from six selected Continuously Operating Reference Stations (CORS). The 1˚x1˚ gridded Vienna Mapping Functions 3 (VMF3) ZTD product and coordinates solutions from the CSRS-PPP positioning service were respectively used as references. The results show that the Black model performed better in estimating the ZTD, followed by Askne and Nordius model. The Saastamoinen, Marini and Murray, Niell, Goads and Goodman and Hopfield models respectively performed poorly. However, the result of the baseline solutions did not show much variation in the coordinate difference provided by the use of the prediction models, nonetheless, the Black and Askne and Nordius models continue to dominate the other models. Of all the models evaluated, either Black or Askne and Nordius model is recommended for use to mitigate the ZTD in the study area, however, the choice of the Black model will be more desirable.
加纳不同对流层延迟模式的比较评价与分析
对流层延迟预测模型在全球导航卫星系统(GNSS)定位应用中发挥着至关重要的作用,因此在GNSS中变得越来越重要。由于地球区域大气条件的不同,对流层对GNSS信号的影响也不同,影响了这些预测模型的性能。因此,选择特定的预测模型会显著降低定位精度,尤其是当模型不适合用户的环境时。因此,对各个地区现有的预测模型进行性能评估,以寻找合适的预测模型是非常必要的。本文利用来自六个选定的连续运行参考站(CORS)的数据,从天顶对流层延迟(ZTD)估计和基线位置精度的角度,评估和分析了加纳常用的七个对流层延迟模型。分别使用CSRS-PPP定位服务的1˚x1˚网格Vienna Mapping Functions 3(VMF3)ZTD产品和坐标解决方案作为参考。结果表明,Black模型在估计ZTD方面表现更好,其次是Askne和Nordius模型。Saastamoinen、Marini和Murray、Niell、Goads以及Goodman和Hopfield的模型分别表现不佳。然而,基线解的结果并没有显示出使用预测模型所提供的坐标差有多大变化,尽管如此,Black、Askne和Nordius模型仍然主导着其他模型。在所有评估的模型中,建议使用Black或Askne和Nordius模型来缓解研究区域的ZTD,然而,选择Black模型将更可取。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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