Orbit Determination of an Uncooperative RSO using a Stereo Vision-Based Sensor

Abstract

Space Situational Awareness (SSA) involves the capability of identification, tracking and characterization of resident space objects. This study considers the use of an inspector spacecraft to autonomously determine the orbit and ballistic coefficient of a resident space object (RSO) in real-time using a stereo vision- based relative navigation sensor when in close proximity with the RSO. Additionally, the inspector spacecraft performs a leader-follower and circumnavigation type formations with the RSO to facilitate 3-D reconstruction of its shape from the visual images. An Unscented Kalman Filter (UKF) is formulated to process raw measurements in the two-dimensional pixel coordinate frame from the visual images of the RSO. The UKF produces relative orbit estimates of the RSO with respect to the inspector in addition to its ballistic coefficient. The UKF uses a novel formulation of relative dynamics that includes differential drag effects and applied thrust accelerations by the inspector spacecraft. The inspector's own orbit and ballistic coefficient are estimated by processing raw GPS pseudorange measurements using an Extended Kalman Filter. The inspector's orbit estimates can be fused with the relative orbit estimates of the RSO to autonomously determine the orbital elements of the RSO. A linear optimal controller is formulated to enable the inspector spacecraft to maintain the RSO in field-of-view of the two cameras as well as to perform leader-follower and circumnavigation type formations. Simulation results showing the feasibility of using stereo vision-based sensors for meeting the above stated SSA objectives and proximity operations are presented.

Meeting Name

23rd AAS/AIAA Space Flight Mechanics Meeting, Spaceflight Mechanics (2013: Feb. 10-14, Kauai, HI)

Department(s)

Mechanical and Aerospace Engineering

Keywords and Phrases

Ballistics; Estimation; Sensors; Space Flight; Space Surveliance; Spacecraft; Stereo Vision

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2013 Univelt Inc., All rights reserved.

Publication Date

01 Feb 2013

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