## 4 Discussion  
Maximum eight SVs contribute to the carrier-based and code-based positioning estimation processes for the GNSS SDR and the commercial U-Blox receiver in the field test in this work. The \(C/N_{0}\) levels have been evaluated in the experiment, and the corresponding results are illustrated in Figure 12. With the assistance of the VT loop and the receiver velocity feedbacks, the tracking loop processing the satellite signal which are confronted with the signal masking problems can manage to tolerate the weak environment for a long time, e.g., the signals from SV8, SV24, and SV32. None of the acquired channels suffers from a signal loss in tracking procedure, and all the channels is being tracked through the whole time spanning of the field test in this work. It can be verified that, the proposed A-VTTCES-KF takes full advantages of the VT technique to help all the tracking channels, without the re-acquisition algorithm, keep working as what the self-contained commercial U-Blox receiver fulfills in a GNSS-challenged environment. Hence, the tracking robustness has been proved to be significantly improved by the A-VTTCES-KF technique. Figure 13 depicts the Doppler estimation results. As mentioned before, the proposed algorithm can remove more unexpected blunders than the ordinary adaptive KF and the baseband signal processing method in the U-Blox receiver. The same conclusions can be drawn through the plots and results in Figure 15. In other words, it can be stated that the A-VTTCES-KF can provide more reliable Doppler observations. Also, the Doppler estimation, which the carrier NCO associated with the PLL updating accounts for, is made use of by the production of the pseudo-range measurement, such that the code-based observation quality is assured to be simultaneously enhanced through the proposed A-VTTCES-KF. The velocities along the east, north, and up directions are illustrated in Figure 14, which indicates that the tested autonomous car is moving and kinematic. Such testing condition could be comparatively challenging and more than enough to verify the performance of the proposed algorithms in this research. The self-designed GNSS SDR sometimes embraces less satellites for positioning than the U-Blox receiver as shown in Figure 16, but it does not mean that the tracking channels which do not participate in positioning perform worse than the counterparts in the U-Blox receiver. Since the GNSS SDR is less self-contained than the U-Blox receiver due to the discrepancy in terms of the entire design strategy. However, this work is not our contribution in the research, and the related information will be not involved with the subsequent discussions. Carrier-based and code-based positioning performances with different algorithms are compared in the experiments and the associated results are plot in Figures 17 and 18, respectively. The positioning results depending on different VT LRs, i.e., 5 Hz, 10 Hz, and 20 Hz, are also computed during the post processing process, and the error curves with respect to the GPS time spanning are displayed in Figures 19 and 20. Since the blunder positioning results could dramatically reduce the accuracy, and such ambiguous results with the contributions of the outliers cannot exactly reflect the real discrepancy among the proposed A-VTTCES-KF and the other ordinary methods. The three-sigma (3\(\sigma\)) rule is adopted to get rid of the unexpected and erroneous solutions, after which the remained positioning data series are subsequently exploited to obtain the corresponding root-mean-square errors (RMSEs).