## 4 Conclusions  
The GPS-based VTTFTB has been successfully upgraded into a multi-GNSS (GPS + Galileo) version. By running HIL simulations of a baseline ESF scenario, the ionospheric remote sensing and EKF estimation capabilities were found to be improved with the addition of Galileo. By comparing to just using the GPS constellation for ionospheric sounding, using GPS (L1, L2) and Galileo (E1, E5b) together decreased the mean and standard deviation of vertical _Ne_ retrieval errors by 32.83% and 46.12% when simulating the 13 July 2018 almanac. A more recent simulation of the 8 March 2019 almanac shows the mean and standard deviation of vertical _Ne_ retrieval errors were decreased further by 43.34% and 49.92% when multi-constellation (GPS and Galileo) data were utilized instead of implementing GPS-only. Using the NovAtel OEM628 receiver, vertical _Ne_ retrieved by the Galileo constellation using E1 and E5a or E1 and E5b TEC are nosier than the _Ne_ retrieved by the GPS constellation using L1 and L2 TEC. The characteristics of retrieved vertical _Ne_ are sensitive to the altitude separation between the two satellites in formation, and \(C/N_{0}\) level. Sufficiently small altitude separation increases measurement noise, while sufficiently large altitude separation reduces spatial resolution. Lower \(C/N_{0}\) level decreases the vertical _Ne_ retrieval accuracy and increases the measurement variance. Ionospheric scintillations from more frequency bands, different power levels and modulation schemes can be observed with the new Galileo system. This offers more opportunities for future GNSS-based SFF missions to detect multi-scale ionospheric irregularities. Also, the relative state estimation performance is increased by using both GPS L1 and Galileo E1 data for differential carrier-phase measurement compared to using GPS L1 only. In order to place onboard GNSS receivers at different altitudes, the formation configurations simulated in the ESF scenario feature a constant radial offset during formation keeping, which is not fuel-efficient especially for small satellite formation flight. Natural relative orbits with bounded motion will be implemented to optimize the fuel budget. To realize an altitude difference between \begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Decrease Percentage of Average Absolute Error** & **Decrease Percentage of Standard Deviation of Error** \\ \hline X & 3.63\% & \(-\)1.78\% \\ Y & 21.06\% & 11.58\% \\ Z & 15.10\% & 20.47\% \\ Vx & 29.87\% & 20.02\% \\ Vy & 26.49\% & 27.83\% \\ Vz & 26.03\% & 37.63\% \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Comparison of relative state estimation errors. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Average Absolute Error** & **Standard Deviation of Error** \\ \hline X (m) & 6.372 & 3.031 \\ Y (m) & 9.373 & 3.393 \\ Z (m) & 2.550 & 0.801 \\ Vx (cm/s) & 0.627 & 11.365 \\ Vy (cm/s) & 0.782 & 1.737 \\ Vz (cm/s) & 0.180 & 0.619 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Relative state errors using GPS. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Component** & **Average Absolute Error** & **Standard Deviation of Error** \\ \hline X (m) & 6.141 & 3.085 \\ Y (m) & 7.399 & 3.000 \\ Z (m) & 2.165 & 0.637 \\ Vx (cm/s) & 0.440 & 1.092 \\ Vy (cm/s) & 0.575 & 1.254 \\ Vz (cm/s) & 0.133 & 0.386 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Relative state errors using multi-constellation GNSS. satellites, elliptic or circular relative orbits should be considered and accessed to characterize the _Ne_ retrieval capability while varying the altitude difference between two LEO satellites. Also, the simulation fidelity of the ionosphere requires some improvement to emulate the ionospheric impacts on GNSS signals more realistically. This will facilitate the design and development of new applications to a wider variety of ionospheric phenomena, such as sub-auroral polarization streams (SAPS), polar tongue of ionization, polar cap patches, ULF waves, etc.