Mitigation of atmospheric effects on GNSS

自1993年以来，24颗或更多的GPS卫星提供了全球覆盖和定位能力。全球定位系统的增强将在不久的将来进行，欧洲基于卫星的导航系统伽利略预计将在2009年投入使用。GPS/伽利略联合能力（一般称为全球导航卫星系统- GNSS）将改善定位性能，促进基于GNSS技术的经济增长。预计到2015年，全球导航卫星系统销售额将达到2000亿美元。为了实现最佳的GNSS定位性能，必须减小测距误差并保持可靠的接收机跟踪能力。分米级定位精度通常是通过利用密集的GNSS参考站区域网络的观测数据对测距误差进行建模来实现的。许多这样的网络正在世界范围内实施。最大的测距误差出现在GNSS信号穿过地球电离层和中性大气时。对于恶劣天气事件和电离层风暴，准确地模拟这些影响是一个挑战。整体的完整性取决于电离层闪烁存在时双频观测的有效性。该提案的重点是为加拿大未来的实时网络RTK应用开发改进的大气模型，并有可能在全球范围内实施。这包括利用新的GNSS发展，确保可靠的接收器跟踪性能，并将新的数据源（例如无线电掩星和NWP）集成到新的建模技术中。本文提出的研究对加拿大发展这一关键技术具有及时和重要的意义。

Since 1993, twenty-four or more GPS satellites have provided worldwide coverage and positioning capabilities. Enhancements to the GPS will take place in the near future and a European satellite-based navigation system, Galileo, is expected to be operational by 2009. Combined GPS/Galileo capabilities (referred to in general as Global Navigation Satellite Systems - GNSS) will allow improved positioning performance and economic growth for GNSS-based technologies. It is anticipated that GNSS sales will reach 200 billion by 2015. In order to achieve optimal GNSS positioning performance, ranging errors must be mitigated and reliable receiver tracking capabilities must be maintained. Decimetre-level positioning accuracies are often achieved by modeling ranging errors using observations from a dense regional network of GNSS reference stations. Many such networks are being implemented worldwide. The largest ranging errors arise as the GNSS signals travel through the Earth's ionosphere and neutral atmosphere. For severe weather events and ionospheric storms, it is a challenge to accurately model these effects. Overall integrity depends on the availability of dual frequency observations in the presence of ionospheric scintillations. The focus of this proposal is the development of improved atmospheric models for future real-time network RTK applications in Canada, with potential for implementation worldwide. This includes capabilities to exploit new GNSS developments, ensure reliable receiver tracking performance, and integrate new data sources (e.g. radio occultations and NWP) into novel modeling techniques. The research proposed here is timely and important for developing this essential technology for Canada.