Multi-Sensor Fusion for Improved Navigation in Lunar Landing Missions

In the last years, a new global interest in Moon exploration has been raised, and both NASA and ESA have started their initiatives. In this respect, all these missions need accurate knowledge of their spacecraft position that almost always relied upon deep-space Earth ground-segment infrastructure. The ESA Lunar Communication and Navigation Services (LCNS) system will provide a oneway service similar to the Global Navigation Satellite System (GNSS), however, since the initial constellation will be composed of a few satellites, the user shall integrate LCNS measurements and further observables. Consequently, sophisticated navigation methods and supplementary sensor measurements shall be employed, such as Inertial Measurement Units (IMUs), altimeters, and optical cameras. The objective of this study is to introduce an approach that utilizes sensor-fusion techniques to integrate diverse observables, while incorporating Vision-Based Navigation (VBN) techniques. The combination of them and VBN contribute provide the user, a lander, with the possibility of computing a very accurate estimation of its position and velocity. Actually, this paper will report the estimation of both the spacecraft state and the receiver clock bias and drift considering the integration of different measurements in a navigation filter and, separately, for the VBN, only the detection phase results will be shown, being matching and position estimation currently under development. The generation of the images and of the Digital Elevation Model (DEM) for the VBN has been done exploiting the Virtual Reality capabilities acquired in the Telespazio Concurrent and Collaborative Design Facility (C2DF). In conclusion, this paper will present the investigated multi-sensor fusion strategy to integrate the LCNS observables with additional sensors and, separately, the VBN and estimate, with a determined accuracy, the lander position along all the different phases of its trajectory.