2013.B.2.2 Autonomous Navigation Using Celestial Object Measurements for a CubeSat Lunar Mission
Danner Friend(1), Jacques Beneat (1)
- Norwich University, USA
Celestial navigation, Autonomous Navigation
The objective of this work was to investigate the feasibility of an attitude and position determination system for a triple CubeSat-sized spacecraft that uses optical sensors for celestial object measurements as input into NASA’s GEONS navigation software. Goddard Space Flight Center has developed a navigation software called GEONS (GPS Enhanced Onboard Navigation System) that includes celestial navigation algorithms for autonomous orbit determination on missions beyond GPS range. The celestial navigation algorithms rely on sensor measurements in the form of line-of-sight (LOS) unit vectors from the spacecraft to celestial bodies such as the Sun, planets, and the Moon. The LOS vector data, the attitude from the star tracker, and the state dynamics model of the orbit provide the necessary information for GEONS to use a recursive filtering process to minimize measurement errors and continuously calculate the best estimate of the spacecraft’s position and velocity. A suite of COTS sensors has been selected to fit within the CubeSat space constraints. The sensors chosen include a star tracker for attitude determination (a required input into the GEONS software), a camera for LOS measurements of the Moon and/or Earth, and sun sensors for LOS measurements of the Sun. The suite of sensors was selected to satisfy the mission requirements for a Lunar mission that is currently in development through a collaborative effort between Vermont Technical College, the University of Vermont, and Norwich University. Matlab code has been developed for image processing of pictures taken of the Moon to determine the LOS vector from the camera to the centroid of the Moon. Although the current analysis is focusing on a Lunar Mission, the celestial navigation capability would be applicable to other interplanetary CubeSat missions.
- Download slides in PDF format here