Abstract:
The increasing interest in the Moon, highlighted by the rapidly growing number of planned lunar missions for the next decade, presents a significant challenge for ensuring reliable communications and navigation. Space agencies worldwide are developing communication and navigation constellations to provide services that enable missions to achieve their objectives. To support its exploration vision, the European space agencies have proposed the Moonlight program to develop a constellation for navigation and communication. This initiative is part of a global effort to create interoperable systems under the LunaNet framework [1].
In this contribution, the performances of the 4 satellites Moonlight constellation will be updated compared to previous works [2], [3], by presenting results assuming the user is equipped with an IMU. This study will first present a high-fidelity modelling of the IMU sensor and of its errors (such as noise and bias terms, scale factors, non-orthogonality and quantization) as well as its integration within the navigation filter. The analyses will then focus on two scenarios, one involving a moving surface rover and the second one on a lunar landing trajectory. Sensitivity analyses to assess the impact of the IMU grade on the user positioning performances will also be performed. Finally, a test case scenario involving IMU measurements faults will be analysed to assess the reliability enhancements that the additional Moonlight measurements can provide to the navigation filter and whether their usage can successfully prevent catastrophic failures such as those of the Mars Schiaparelli probe.
Bibliography:
[1] NASA; ESA; JAXA, “Draft 5 LunaNet Interoperability Specifications,” 2025.
[2] Y. Audet, F. T. Melman, D. V Psychas, R. D. Swinden, and J. Ventura-Traveset, “Positioning of a Lunar Lander using a dedicated Lunar Communication and Navigation System assuming realistic ODTS performances,” 2023. doi: 10.3390/0.
[3] Y. Audet et al., “Positioning of a lunar surface rover on the south pole using LCNS and DEMs,” Advances in Space Research, vol. 74, no. 6, pp. 2532–2550, Sep. 2024, doi: 10.1016/j.asr.2024.06.022.