Inertial Properties Estimation of a Passive On-orbit Object Using Polhode Analysis

Many objects in space are passive, with unknown inertial properties. If attempting to dock autonomously to an uncooperative object (one not equipped with working sensors or actuators), a motion model is required to predict the location of the desired docking location into the future. Additionally, f...

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Bibliographic Details
Main Authors: Setterfield, Timothy Philip, Miller, David W, Saenz Otero, Alvar, Frazzoli, Emilio, Leonard, John J
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Format: Article
Language:en_US
Published: American Institute of Aeronautics and Astronautics 2018
Online Access:http://hdl.handle.net/1721.1/117602
https://orcid.org/0000-0002-0692-8665
https://orcid.org/0000-0001-6099-0614
https://orcid.org/0000-0002-0505-1400
https://orcid.org/0000-0002-8863-6550
Description
Summary:Many objects in space are passive, with unknown inertial properties. If attempting to dock autonomously to an uncooperative object (one not equipped with working sensors or actuators), a motion model is required to predict the location of the desired docking location into the future. Additionally, for cooperative satellites that failed to deploy hardware, accurate knowledge of the object’s principal axes and inertia ratios may aid in diagnosing the problem. This paper develops algorithms for estimation of the analytical motion model, principal axes, and inertia ratios of a passive on-orbit object. The polhode of the object is estimated visually (for uncooperative targets) or with gyroscopes (for cooperative targets). Estimation of the principal axes is performed by calculating the body frame orientation for which ellipses and hyperbolas optimally fit the projections of the polhode onto the principal planes. Given the polhode in the object’s body frame, constraints are used to restrict the feasible inertia ratios to a single degree of freedom. Constrained optimization is then used to estimate the inertia ratios. The algorithms are validated using visual and gyroscope data from the SPHERES-VERTIGO test platform on the ISS and visual data from simulation.