Estimation of code ionospheric biases using Kriging method

The code ionospheric bias, also known as the Differential Code Bias (DCB), is an important correction term for single-frequency receiver. This paper proposes a new method to estimate the biases as well as the vertical ionospheric delays using Kriging estimator with a network of receivers. Kriging estimates an unknown variable based on a set of known parameters and a variogram describing the spatial correlation. It is the best estimator in the sense of minimizing the estimation variance.

Kriging method is proposed, as it could reconstruct the vertical delays based on a subset to overcome the rank deficiency. A Kalman filter is introduced, and a sub-optimum solution has been obtained based on an iterative Greedy Algorithm. Simulation results have shown cm-level accuracy on the ionospheric bias estimates. The algorithm has also been applied with real GPS data for multiple days, which showed high bias repeatability. The bias estimates have been verified by comparison with published values.

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