Presenter Information

Forrest Rogers-Marcovitz

Session

Session VIII: 17th Annual Frank J. Redd Student Scholarship Competition

SSC09-VIII-1.pdf (538 kB)
Presentation Slides

Abstract

Proximity operations between spacecraft allows for docking, inspection, and repair of a target vehi- cle. Very small spacecraft, under 20 kg, are well- suited for proximity activities and are of growing in- terest in the aerospace community. However, due to size and power constraints, small vehicles can- not carry traditional precision navigation systems and have generally noisy sensor and actuator op- tions. This paper presents two techniques for im- proved autonomous, on-board navigation that ac- count for noisy and poorly observable states. First, an Unscented Kalman Filter is implemented for lo- calization which incorporates orbital dynamics and quaternion rotation. Second, two online regres- sion algorithms, Bayes Linear Regression and Gaus- sian Process Regression, are used to learn the time- varying thruster dynamics. These techniques have been demonstrated successfully on a simulated small inspector vehicle and are being integrated on the Washington University in St. Louis Bandit inspec- tor spacecraft.

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Aug 12th, 10:45 AM

Online Dynamic Modeling and Localization for Small-Spacecraft Proximity Operations

Proximity operations between spacecraft allows for docking, inspection, and repair of a target vehi- cle. Very small spacecraft, under 20 kg, are well- suited for proximity activities and are of growing in- terest in the aerospace community. However, due to size and power constraints, small vehicles can- not carry traditional precision navigation systems and have generally noisy sensor and actuator op- tions. This paper presents two techniques for im- proved autonomous, on-board navigation that ac- count for noisy and poorly observable states. First, an Unscented Kalman Filter is implemented for lo- calization which incorporates orbital dynamics and quaternion rotation. Second, two online regres- sion algorithms, Bayes Linear Regression and Gaus- sian Process Regression, are used to learn the time- varying thruster dynamics. These techniques have been demonstrated successfully on a simulated small inspector vehicle and are being integrated on the Washington University in St. Louis Bandit inspec- tor spacecraft.