Lee Jinsil, Lee Jiyun
Department of Aerospace Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-Ro, Daejeon 305-701, Korea.
Sensors (Basel). 2019 May 8;19(9):2127. doi: 10.3390/s19092127.
An ionospheric spatial decorrelation is one of the most dominant error factors that affects the availability of safety-critical differential global navigation satellite systems (DGNSS). This is because systems apply significant conservatism on the error source when ensuring navigation safety due to its unpredictable error characteristic. This paper investigates a correlation between GNSS-derived ionospheric spatial decorrelation and space weather intensity. The understanding of the correlation has significant advantages when modeling residual ionospheric errors without being overly pessimistic by exploiting external sources of space weather information. An ionospheric spatial decorrelation is quantified with a parameter of spatial gradient, which is an ionosphere total electron content (TEC) difference per unit distance of ionospheric pierce point (IPP). We used all pairs of stations from dense GNSS networks in the conterminous United States (CONUS) that provide an IPP separation distance of less than 100 km to obtain spatial gradient measurements under both ionospherically quiet and active conditions. Since the correlation results would be applied to safety-critical navigation applications, special attention was paid by taking into consideration all non-Gaussian tails of a spatial gradient distribution when determining spatial gradient statistics. The statistics were compared with space weather indices which are disturbance storm time (Dst) index and interplanetary magnetic field (IMF) Bz index. As a result, the ionospheric spatial decorrelation showed a significant positive correlation with both indices, especially under active ionospheric conditions. Under quiet conditions, it showed positive correlation slightly weaker than those under active conditions, and the IMF Bz showed preceding response to the spatial gradient statistics revealing the potential applicability for predicting the spatial decorrelation conditions.
电离层空间去相关是影响安全关键型差分全球导航卫星系统（DGNSS）可用性的最主要误差因素之一。这是因为由于其不可预测的误差特性，系统在确保导航安全时对误差源采用了显著的保守性。本文研究了全球导航卫星系统（GNSS）导出的电离层空间去相关与空间天气强度之间的相关性。通过利用外部空间天气信息源对残余电离层误差进行建模而不过度悲观时，对这种相关性的理解具有显著优势。电离层空间去相关用空间梯度参数来量化，该参数是电离层穿刺点（IPP）每单位距离的电离层总电子含量（TEC）差异。我们使用了美国本土（CONUS）密集GNSS网络中所有站对，这些站对提供的IPP分离距离小于100公里，以获取电离层平静和活跃条件下的空间梯度测量值。由于相关结果将应用于安全关键型导航应用，在确定空间梯度统计量时，通过考虑空间梯度分布的所有非高斯尾部给予了特别关注。将这些统计量与空间天气指数进行了比较，这些指数是扰动风暴时间（Dst）指数和行星际磁场（IMF）Bz指数。结果表明，电离层空间去相关与这两个指数都呈现出显著的正相关，特别是在电离层活跃条件下。在平静条件下，其正相关性略弱于活跃条件下的，并且IMF Bz对空间梯度统计量呈现出超前响应，揭示了其在预测空间去相关条件方面的潜在适用性。
