## 3 Experiment
### Performance Analysis of TDCP-Aided GNSS with Method B  
The contribution of method B is to adjust the measurement weights adaptively. In this case, the influence of inconsistent measurements can be reduced, and the estimated position becomes closer to the designated path in comparison with TDCP-based GNSS. For instance, In Figures 8 and 11 (scenario A and D, during time 525-540 s and 877-884 s), the solution with method B (green and black lines) showed superior robustness during the operation in challenging environments, whereas the solutions without method B misdirected the vehicular path towards an oncoming-traffic road. In Figure 9 (scenario B, time 815 s), the positional distortion due to the multipath/NLOS contamination was improved after the intervention of method B, even when the TDCP-aided approach was inactive. However, unsatisfactory estimation was still found in static situations. Although the performance of the TDCP-based solution with method B in the stationary condition was superior to the typical solutions without it (cyan and orange lines), the present finding exhibits that the remaining error was still up to 13.47 m in the horizontal direction (scenario B, time 853 s) and 10.62 m in the vertical direction (scenario C, time 932 s) for the harsh cases. This situation was attributed to the increase in the number of abnormal signals for the stationary condition. Another discussed case was in the GNSS-outage environment, as shown in Figure 12 (area I of scenario E, during time 1945-1954 s). In this area, the aid of method B was not obvious, where the positional error reached a maximum of up to 8.95 m and 5.43 m in the horizontal and the vertical directions. That was because method B failed to find appropriate scales for reweighting. Taking the situation of time 1  
1636-1663 s), this combined scheme mitigated the limitation of method B and prevented the related error growth, and the maximum of the remaining error for these areas was reduced by approximately 8.93 m, 5.97 m, and 2.91 m in the horizontal direction, and 2.71 m, 8.04 m, and 3.99 m in the vertical direction, respectively. According to the previous results, it can be found that: (1) method B provides improved position before the dynamical motion transits to stationary, and therefore, method A can provide a superior position-fix result. (2) method A effectively averts the degradation of continuous reception of abnormal signals (where method B is limited) and maintains the performance under stationary motion. According to the statistical analysis (Table 3), the TDCP-based GNSS with both methods showed an RMSE of 4.06 m in 3D with an improvement of 51.4% under the static condition. The maximum error in 3D improved from 37.24 m (conventional solution) to 8.88 m, which is significantly better than the performance based on method A only (12.45 m). The other significant advantage of the combined method is in the frequent GNSS-outage environment. In Figure 12 (area I of scenario E, during time 1945-1954 s), the unsatisfactory performance was improved by 63.2% and 82.3% at most in the horizontal and vertical directions in contrast with method B. The main reasons are the following mechanisms from both methods in this area: (1) odometer-aided robust regression, providing a more reliable scale for reweighting and more accurate position state (compared with method B only) before driving into the GNSS-degraded environment (epochs before time 1948 s); (2) odometer-based FDE, averting unsatisfactory position state estimation due to the majority of faulty signals; (3) odometer-aided DR, bridging the duration of GNSS outage. The combined performance significantly increased the availability of satisfactory results in such a harsh situation.