B2.2 Introducing pseudo-range rates and IMU sensors to improve lunar satellite navigation system performance

In recent years, interests in lunar exploration have surged significantly, making accurate and reliable navigation crucial for the success of current and future lunar missions.

Extensive research has been conducted on Moon satellite navigation systems, and, for example, the Moonlight project was launched by the European Space Agency, aimed at developing the first satellite navigation system around the Moon. Recent works investigated different types of constellations and localization methods, with the most promising solution considering ELFO orbits and pseudo-range measurements. Moreover, to overcome the limitations due to the small number of satellites in the initial phase of a constellation deployment, several solutions have been proposed, like adding the use of additional RTD measurements and/or an altimeter on board.

This work investigates the use of other measurements/sensors, i.e. pseudo-range rate and Inertial Measurement Unit (IMU), to further improve the performance of the system and to reach the availability and accuracy needed for demanding applications, such as Moon landing.

An Extended Kalman Filter (EKF) is proposed to integrate all the possible measurements combinations (pseudo-range, pseudo-range rate, altimeter, IMU accelerations) and to estimate position, velocity, and time (PVT) of the user receiver. Two initial operational modes are considered: (a) relying on the traditional pseudo-range localization, and (b) enhanced localization, that is, incorporating RTD and altimeter. These two modes are improved with the addition of pseudo-range rates and IMU and the performances are evaluated to choose the best possible solution.

The performance analysis focuses on minimizing the position and velocity estimation errors and on the evaluation of the improvement of robustness of the overall system. Particular attention is posed near ill-conditions or singularity points, where the two base modes show some limitations. The evaluation uses Montecarlo runs on different trajectories, representing possible spacecraft landing paths or a rover moving on the Moon surface.

The simulation results, show an error reduction of about 25% in terms of position estimation with pseudo-range rate and up to about 60% with the addition of IMU measurements w.r.t. the original performances.

Moreover, the introduction of pseudo-range rates and IMUs reduces the velocity estimation errors by up to 95%, significantly enhancing the velocity estimation accuracy, particularly useful in landing management.

Last but not least, the localization performances are greatly improved near and in ill-condition points or near singularity, improving the robustness of the system also in the initial deployment phase of the navigation system.