Ionospheric Refraction Estimation from Smartphone GNSS Measurements

Ionospheric refraction contribute significant errors to global navigation satellite systems(GNSS) measurements. Corrections for these errors are determined empirically based on their measured effect on GNSS signals. However, typical methods of determining corrections utilize incredibly costly geodetic receivers, and publicly available corrections lack robust spatial and temporal resolution. As such, ionospheric refraction estimates and corrections derived from dual-frequency capable smartphones have been explored in the literature, with corrections estimated from static data collected in open sky environments. However, real-world smartphone data collection conditions deviate significantly from these ideal cases. For example, a typical urban environment has increased noise from large multipath errors, susceptibility to signal loss, and smartphones are rarely kept oriented in a stable static positions. Thus, this paper attempts to introduce methods aimed at increasing the precision and accuracy of real-world smartphone slant ionospheric refraction estimates to allow for improved estimates derived from multismartphones. Results presented demonstrate capabilities for smartphone hardware bias estimation and correction over short periods with overall root mean square error (RMSE) reductions of multiple meters when comparing smartphone and geodetic reference estimates. Additionally, filtering and data smoothing are applied with results consistently reducing standard deviations of smartphone slant ionospheric estimates by over 50%. Furthermore, a multi-smartphone solution between two phones is implemented with results showing a 30% decrease in RMSE between raw smartphone estimates and their geodetic reference, and final filtered RMSE values in the sub-meter level. Based on these results, an increased number of smartphones is expected to provide even further increases to ionospheric refraction estimate performances.