# A Study of Cislunar-Based Small Satellite Constellations with Sustainable Autonomy
## 6 Discussions
Figure 11d displays the variation of inclination of the constellation orbits with Azimuth and Elevation angles, respectively. This is as significant as monitoring RAAN for Earth due to perturbations. The SRP and in-orbit satellite-to-satellite lunar perturbations have a greater impact on the inclinations of the satellites in a constellation and can even change the orientation of an entire constellation. Hence, Figure 11d's variation with inclination and ground parameters signifies the variation of the satellites in healthy conditions over the lunar surface at the given altitudes. The fold shown in the plot is due to the turnaround of the satellite to re-take its position after moving over an approaching target ground station after the contact, moving away from it, retaining the orbit autonomously, and repeating the process. Figure 11e,f is dedicated to the ground parameters' variations with the approaching satellites. Now, for the Moon, there is a slight difference from what is attained for Earth. The perspectives of the ground and satellite are crucial due to the placement of satellites in a hybrid form of constellation distant from the Earth's surface. For instance, Figure 11e shows the variation of the satellite's (Sat1 and Sat8) Azimuth and Elevation with respect to the approaching ground stations, whereas Figure 11f shows the variations of the Azimuth and Elevation angles of the ground station with respect to the approaching satellites (Sat4 and Gateway). This is important to differentiate the operating parameters and align them with respect to the given situation in orbit and on the ground (when the settlements happen on the Moon with a significant number of landings). Figure 12 gives insights into the Monte Carlo analysis for the Moon's side of collision chances (probability) in its orbital space. The methodology remains the same with due consideration to the local environment. It can be closely observed that Figure 12a has a sharp variation with 2000 random states and the number of misses varies randomly, as shown in Figure 12b, with situations of Debris and Mission collisions included. These variations are much different from what is observed in this analysis of the Earth scenario. The major reason for this is obviously the intensity of congestion over the Earth and over the Moon are widely distinct. The reason is that the algorithm has a fewer number of random states to iterate and speed up the progression with iterations to find the solution sharply and tends to linearize as an optimal solution is found at the end of propagation. The fewer number of random states doesn't signify a less impactful form of analysis or prediction for a probable collision with respect to the method used. It only indicates that the number of probable collisions is less stable and needs to be balanced with appropriate autonomy to make the best solution for a particular situation during operations. Figure 12c,d, on the other hand, gives more confidence in the solution and determines a much stronger and impactful prediction of a probable collision. These also need to be balanced and integrated into autonomy for synergizing decisions with ground control and navigating safely, avoiding any collision or near pass-by of another mission or debris. This is evident in Figure 12c, which shows impactful stability after a collision was predicted to its avoidance successfully in orbit. Figure 12d shows the strongest probable number of misses initially, and then the number reduces after the action was taken and the satellite continues its normal operations. Tables 5 and 6 show positive percentage changes in the probability of collision difference from nominal to Monte Carlo predictions. This indicates that the probability of collision iterations remains below zero at all times the instance of  
probable collision occurred. Hence, the change is observed and the possible danger is overcome with due coordination of the autonomy.