Analysis of factors affecting the estimation of the multi-GNSS satellite differential code biases (SDCBs)

Abstract

The satellite hardware differential code biases (SDCBs) are one of the important factors affecting the accuracy of GNSS-based ionospheric total electron content (TEC) estimation. The accuracy of SDCB estimates is directly influenced by the data processing methodology. To analyze the impact of various factors on multi-GNSS SDCB estimation, we conducted a comprehensive analysis of the number of contributed stations, the data sampling rate, the contributed satellite systems, and the cut-off elevation angle. Two sets of GNSS data obtained from the International GNSS Service (IGS) multi-GNSS experiment (MGEX) network, covering both high and low solar activities during the ascending phase of solar cycle 25, were processed to estimate multi-GNSS SDCBs. The results indicate that the number of contributed stations is the primary factor that influences multi-GNSS SDCB estimation. To achieve a balance between computational efficiency and accuracy, a data sampling rate of 540 s is recommended, which results in a multi-GNSS SDCB root-mean-square (RMS) error of less than 0.01 ns compared to a 60-second sampling rate. The stability of SDCBs is hardly affected by incorporating observations from multiple GNSS systems, and the differences of the standard deviations of SDCBs for quad-, triple- and dual-system solutions are below 0.002 ns. Additionally, the results indicate that the optimal cutoff elevation angle for multi-GNSS SDCB estimation is between 20° and 30°, which ensures the best stability in the estimated multi-GNSS SDCBs.