Session B4b: Future of Space, Lunar, and Extraterrestrial Navigation 2

Optimal Lunar Rover Navigation with LANS: Leveraging 3D PNT Simulation and Nonlinear Optimization for Enhanced Trajectory Planning
Ricardo Verdeguer Moreno, Ivan Acosta Bayona, Spirent Communications PLC; Cesar Enselme, Oktal-SE
Location: Holiday 4-5 (Second Floor)
Date/Time: Thursday, Sep. 11, 2:12 p.m.

Best Presentation

As humanity prepares for sustained lunar exploration, the development of robust Positioning, Navigation, and Timing (PNT) systems suitable for Moon applications becomes critical. This presentation explores state-of-the-art lunar PNT 3D simulation, showcasing advancements in multi-domain modelling that integrates orbital dynamics, signal propagation, and lunar surface interactions. This capability is vital for testing concepts such as Earth-based GNSS for cislunar applications, the design of new lunar satellite constellations, and hybrid solutions combining ground-based and orbital systems on the Moon.
Our presentation features initial results from an ongoing collaboration with JAXA, including an analysis of PNT signal reception 3D heatmaps across key lunar locations such as Connecting Ridge, Shackleton Rim, and Shackleton Peak. These high-fidelity 3D simulations provide crucial insights into coverage patterns, signal availability, and performance variations driven by lunar topography, satellite orbits, and mission-specific constraints.
A key aspect of our research is the application of optimal control theory to lunar rover navigation, where we leverage the large-scale nonlinear solvers to compute optimal rover trajectories based on lunar PNT signal heatmaps. These trajectories are designed to maximize navigation accuracy by incorporating PNT signal parameters such as visibility and Geometric Dilution of Precision (GDOP) from the Lunar Augmented Navigation Service (LANS) while also accounting for the rover’s dynamic constraints, including velocity, acceleration, and manoeuvrability.
By combining high-fidelity PNT 3D simulations with advanced optimization techniques, we aim to support the development of resilient lunar navigation architectures for a wide range of applications, from crewed landings to robotic exploration and resource extraction.