Autonomous Optical Navigation for the Lunar Meteoroid Impacts Observer

Abstract

CubeSats are low-cost platforms to test innovative technologies in-flight that also allow performing science [1].Adopting CubeSats is appealing due to the inherent savings in the design, production, and launch costs. While these costs scale with the mass, power, and size of the platforms, those related to operations do not obey the same trend. Navigation is among those operations that are performed routinely, regardless of the mission phase. Deep-space probes are usually navigated through ground-based radiometric tracking and orbit determination [2], which contribute significantly to the ground segment costs. Granting autonomous on-board navigation is instrumental to reducing the overall mission cost of small probes, and to pave the way for novel deep-space mission concepts [3].The Lunar Meteoroid Impacts Observer, or LUMIO, is a 12U CubeSat mission to observe, quantify, and characterize the meteoroid impact flux by detecting their impact flashes on the lunar far-side [4]. LUMIO was awarded ex-aequo winner of the European Space Agency's challenge LUCE (Lunar CubeSat for Exploration), under the SysNova framework § . An independent assessment conducted at ESA's Concurrent Design Facility (CDF) has proven the mission feasible ¶ , and as such LUMIO is currently being considered for future implementation. LUMIO is placed in a quasi-halo orbit about Earth-Moon L 2 [5], as shown in Figure 1a-1b. From this orbit, full-disk images of the lunar farside are acquired through the LUMIO-Cam, an optical instrument capable of detecting meteoroid impact flashes in the visible spectrum. As a secondary application of the scientific investigation, the LUMIO-Cam is used to navigate autonomously, employing the Moon full-disk images to perform horizon-based navigation [6]. This technique resembles the backup navigation in Exploration Mission 1 [7]. The spacecraft state is estimated without relying on ground station tracking. Demonstrating this capability is the major technological objective of LUMIO. This note describes the methods and tools developed to quantify the performances of the full-disk optical navigation in LUMIO. The horizon-based method [8] has been embedded into a simulator that generates synthetic Moon images via a ray tracer software. The position vector is then filtered to estimate the whole spacecraft state. Errors in the state, dynamics, and maneuver execution have been considered. Preliminary results show feasibility of the devised concept of operation for autonomous navigation and station keeping: requirements on position and velocity knowledge are satisfied.

Nonlinear Estimation for Autonomous Optical Navigation

“…Other studies have examined similar scenarios, Christian and Lightsey [23], used a EKF for autonomous OpNav in a planetary flyby of Venus. Franzese et al [24], explored using an EKF for the LUMIO CubeSat mission. While, Paluszek et al [25], implemented a UKF into a optical navigation system for use in a wide variety of missions.…”

High-fidelity trajectory design to flyby near-Earth asteroids using CubeSats

“…In the interest of a low-cost mission, it would be advantageous to autonomously perform orbit determination around L1/L2, to minimize ground support. As an example, the 12U LUMIO mission is expected to autonomously navigate around the Earth-Moon L2 point [49]. Further analysis, however, shall be performed to determine whether autonomy can also be achieved around the Sun-EMB Lagrange points and with a smaller spacecraft.…”

Deep-Space Optical Navigation Exploiting Multiple Beacons

“…The X-ray pulsars navigation relies on the repetitive signals coming from X-ray pulsars to estimate the observer distance with respect to the solar system barycenter [2,21]. The optical navigation in proximity of a celestial object exploits the target knowledge to determine the observer position, finding applications in the lunar environment (e.g., full-disk navigation [6,8,15], terrain relative navigation [7]), small body proximity (e.g., landmark navigation [3]), and satellite proximity (e.g., pose estimation [17]). The optical navigation in deep-space leverages on the acquisition of the line-of-sight (LoS) directions to deep-space objects with known ephemeris to determine the observer position [4,10,11,14].…”