## 4 Test and Result
### Adaptive Strategy Test  
The variation and statistics of KBW are shown in Figure 4. The AMC-KF is proved to be effective as the KBW increases rapidly after initialization to respond to the input GNSS measurements and varies epoch by epoch. In Figure 4b, the mean and standard deviation found for (STNY-NEWH, QCLF-ANGS, NEWH-BONE, BONE-STNY, BONE \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multirow{2}{*}{**Baseline**} & \multicolumn{2}{c}{**E**} & \multicolumn{2}{c}{**N**} & \multicolumn{2}{c}{**U**} & \multirow{2}{*}{**Improvement on ENU**} \\ \cline{3-3} \cline{5-10}  & & **AMC-KF** & & & & & & & & & \\ \hline \multirow{4}{*}{RMSE (m)} & BONE-QCLF & 0.13417 & 0.28258 & 0.20254 & 0.43671 & 0.30294 & 0.80099 & +52.52\%, +53.62\%, +62.18\% \\ \cline{2-10}  & QCLF-ANGS & 0.09421 & 0.23641 & 0.17402 & 0.23035 & 0.27439 & 0.96756 & +60.15\%, +24.45\%, +71.64\% \\ \cline{2-10}  & ANGS-BONE & 0.16395 & 0.53574 & 0.18714 & 0.15190 & 0.26284 & 0.65454 & +69.40\%, \(-\)23.20\%, +59.84\% \\ \hline \multirow{4}{*}{STD (m)} & BONE-QCLF & 0.10886 & 0.10066 & 0.18606 & 0.33062 & 0.30278 & 0.40077 & \(-\)8.15\%, +43.72\%, +24.45\% \\ \cline{2-10}  & QCLF-ANGS & 0.08226 & 0.11478 & 0.16659 & 0.17340 & 0.26107 & 0.52163 & +28.33\%, +3.93\%, +49.95\% \\ \cline{2-10}  & ANGS-BONE & 0.16027 & 0.23124 & 0.16694 & 0.10958 & 0.24867 & 0.53847 & +30.69\%, \(-\)52.35\%, +53.82\% \\ \cline{2-10}  & BONE-STNY & 0.15830 & 0.35895 & 0.15017 & 0.42681 & 0.19493 & 1.32102 & +55.90\%, +64.82\%, +85.24\% \\ \cline{2-10}  & STNY-NEWH & 0.13166 & 0.10709 & 0.13620 & 0.34410 & 0.19730 & 1.21688 & \(-\)22.94\%, +60.42\%, +83.79\% \\ \cline{2-10}  & NEWH-BONE & 0.17273 & 0.37092 & 0.13468 & 0.77698 & 0.19800 & 0.60796 & +53.43\%, +82.67\%, +67.43\% \\ \hline \multirow{4}{*}{STD (m)} & BONE-STNY & 0.13460 & 0.19663 & 0.14762 & 0.27757 & 0.18249 & 0.85175 & +31.55\%, +46.827\%, +78.57\% \\ \cline{2-10}  & STNY-NEWH & 0.11695 & 0.10515 & 0.13590 & 0.21013 & 0.19655 & 0.42460 & \(-\)11.22\%, +35.33\%, +53.71\% \\ \cline{1-1} \cline{2-10}  & NEWH-BONE & 0.10496 & 0.19900 & 0.13333 & 0.50321 & 0.19746 & 0.58359 & +47.26\%, +73.50\%, +66.16\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: RMS and STD improvement on ENU for BONE-QCLF-ANGS-BONE. Figure 3: RODP and available satellites of BONE. QCLF) are (16.1284, 14.9827, 20.6101, 19.1174, 13.1624, 17.0062) and (4.7120, 5.1061, 6.1030, 5.4980, 3.9002, 5.38731), respectively. Although the KBW is different from each other as all baselines are spatially separated, the similar variation trend verified that the adaptive KBW is sensitive to the environment. The filter time consumption with the proposed adaptive KBW and the original fixed KBW in MCC is illustrated in Figures 5 and 6. The fixed KBW used here is set to be 1, 5, 25, and 30, as all KBW has shown in Figure 4b fall in [0, 30]. It could be found that the adaptive KBW owns smoother and more stable processing results. It means that the embedded devices and on-chip modules may benefit from power conservation [1]. For adaptive KBW, the average time consumption at each epoch is (0.0683 s, 0.0535 s, 0.0520 s, 0.0674 s, 0.0641 s, 0.0495 s) on ANGS-BONE, BONE-QCLF, BONE- STNY, NEWH-BONE, QCLF-ANGS, STNY-NEWH. While for fixed KBW (1, 5, 25, 30) are (0.0619 s, 0.0599 s, 0.0717 s, 0.0659 s), (0.0528 s, 0.0549 s, 0.0517 s, 0.0544 s), (0.0515 s, 0.0543 s, 0.0581 s, 0.0582 s), (0.0542 s, 0.0681 s, 0.0680 s, 0.0543 s), (0.0658 s, 0.0594 s, 0.0679 s, 0.0662 s) and (0.0581 s, 0.0560 s, 0.0574 s, 0.0499 s), respectively. Figure 4: KBW time series and statistics for each baseline. (**a**) Time series for each baseline; (**b**) the statistics of KBW time series. Figure 5: Time consumption with different KBW strategies on ANGS-BONE, BONE-QCLF, BONE-STNY. Treating adaptive KBW as the benchmark, the efficiency improvement is demonstrated in Figure 7. For all 24 cases, negative values (shown in nine cases) indicate a longer time consumption than the benchmark, and the positive values (shown in 15 cases) indicate the opposite results.