Automated daily processing of more than 1000 ground‐based GPS receivers for studying intense ionospheric storms

Abstract

[1] As the number of ground-based and space-based receivers tracking the Global Positioning System (GPS) satellites steadily increases, it is becoming possible to monitor changes in the ionosphere continuously and on a global scale with unprecedented accuracy and reliability. As of August 2005, there are more than 1000 globally distributed dual-frequency GPS receivers available using publicly accessible networks including, for example, the International GPS Service and the continuously operating reference stations. To take advantage of the vast amount of GPS data, researchers use a number of techniques to estimate satellite and receiver interfrequency biases and the total electron content (TEC) of the ionosphere. Most techniques estimate vertical ionospheric structure and, simultaneously, hardware-related biases treated as nuisance parameters. These methods often are limited to 200 GPS receivers and use a sequential least squares or Kalman filter approach. The biases are later removed from the measurements to obtain unbiased TEC. In our approach to calibrating GPS receiver and transmitter interfrequency biases we take advantage of all available GPS receivers using a new processing algorithm based on the Global Ionospheric Mapping (GIM) software developed at the Jet Propulsion Laboratory. This new capability is designed to estimate receiver biases for all stations. We solve for the instrumental biases by modeling the ionospheric delay and removing it from the observation equation using precomputed GIM maps. The precomputed GIM maps rely on 200 globally distributed GPS receivers to establish the ''background'' used to model the ionosphere at the remaining 800 GPS sites.Citation: Komjathy, A., L. Sparks, B. D. Wilson, and A. J. Mannucci (2005), Automated daily processing of more than 1000 ground-based GPS receivers for studying intense ionospheric storms, Radio Sci., 40, RS6006,

Consistency of seven different GNSS global ionospheric mapping techniques during one solar cycle

“…GIM is a data-driven model that uses a Kalman filter-based approach to fit the observed slant TEC (STEC) observations from the ground-based receivers to a model that is described by a set of horizontal basis function coefficients (e.g. [28]; [29], [25], [24]). A single bias for each GPS satellite and each receiver is estimated when using GPS observables alone.…”

Statistical framework for estimating GNSS bias

“…In this case, the theory matrix will only have at most two nonzero elements for each row. For GPS receivers, satellite biases are known to a good accuracy using a separate and comprehensive analysis technique (Komjathy et al, 2005), and therefore this special case is appropriate for bias determination for GPS receivers.…”

First storm‐time plasma velocity estimates from high‐resolution ionospheric data assimilation

“…[27] The upper plots in Figure 6 show the dual-frequency CORS observations of slant TEC over time for (a) GARF and (b) WOOS with a blue solid line. These dual-frequency data were processed to level satellite and receiver interfrequency biases by Jet Propulsion Lab Global Ionospheric Mapping (GIM) tool [Komjathy et al, 2005]. The GIM tool has been used routinely and robustly for many scientific campaigns and was used to produce the TEC map in Figure 1.…”