Improving PVT Estimation for Safe Lunar Landing Missions

Moon exploration has emerged as a significant frontier in the era of space commercialization in recent years, with many public and private entities showing growing interest and investment in lunar missions. This increase in lunar and cislunar activities has prompted outstanding initiatives promoted by NASA and the European Space Agency (ESA). Historically, lunar missions have relied on deep-space Earth ground-segment infrastructures to obtain accurate knowledge of the spacecraft trajectory, but today, many studies are being conducted to demonstrate improvements in user position, velocity and timing (PVT) estimation enabled by a navigation constellation around the Moon. The objective of this study is to describe an approach that uses sensor-fusion techniques based on a tightly-coupled Extended Kalman Filter (EKF) to integrate lunar GNSS-like one-way ranging (OWR) signals with a wide range of on-board observables, such as inertial measurement units (IMU), altimeters, twoway ranging (TWR) with an orbiter in Elliptical Lunar Frozen Orbit (ELFO) and visual-based navigation (VBN) techniques for estimating both the spacecraft state and the receiver clock bias and drift, in different phases of a lunar landing at the Shackleton Rim.