Abstract

As one of the important factors influencing the ionospheric total electron content (TEC) estimation accuracy, receiver differential code biases (DCBs) should be properly removed from global navigation satellite system (GNSS) measurements. The intraday variability in receiver DCBs (rDCBs), which is usually ignored in the commonly used ionospheric observable retrieval procedure, has been identified as one of the major errors degrading the accuracy of TEC estimation. The modified carrier-to-code leveling (MCCL) method can be adopted to eliminate the impact of the rDCB variability on the retrieval of the ionospheric TEC from dual-frequency (DF) GNSS observations. In this contribution, we extend the MCCL method from two aspects. First, the DF MCCL method is adapted to the multi-frequency (MF) case, in which DF, triple-frequency or even arbitrary-frequency observations can be readily processed to simultaneously estimate both the ionospheric TEC and rDCB variations. Second, the MCCL method is refined to enable the handling of GLONASS data by accounting for the effects of code inter-frequency biases induced by the frequency division multiple access (FDMA) technology. Based on the test results, the retrieval accuracy of the ionospheric TEC using our proposed method can be improved from 9.47 TECu to 2.67 TECu in the presence of significant intraday rDCB variations. We discovered that the maximum difference in the rDCB variations of the same satellite system between different frequency bands can be as large as 10 ns. The dependence of multi-GNSS and MF rDCB variations on the ambient temperature is further verified in this study. The results show that the temperature dependence of rDCB varies among different satellite systems and frequency bands. Compared to the Galileo, GPS and GLONASS satellite systems, the Beidou system (BDS) rDCB estimates exhibit a stronger correlation with the measured temperature. The percentages of stations with the mean absolute Pearson correlation coefficient value above 0.8 are 27.17% for GPS, 30.58% for GLONASS, 43.78% for BDS and 33.9% for Galileo, respectively.

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