High-Accuracy, Vision-Based Attitude Estimation System for Air-Bearing Spacecraft Simulators

Abstract

Air-bearing platforms for simulating the attitude dynamics of satellites require highly accurate ground truth systems. Commercial off-the-shelf motion-capture systems are used for this scope, although they are complex and expensive. This paper shows a novel and versatile method to estimate the attitude of rotational air-bearing platforms using a monocular camera and sets of fiducial LED markers. The work proposes a geometry-based, iterative algorithm that is significantly more accurate than other literature methods that involve solving the perspective-[Formula: see text]-point problem. Additionally, autocalibration procedures to perform a preliminary estimation of the system parameters are shown. The developed methodology is deployed onto a Raspberry Pi 4 microcomputer and tested with an array of LEDs soldered on a custom printed circuit board. Data obtained with this setup are compared against simulations of the system to determine and validate its performance. The hardware setup is also validated against independent inclinometric and gyroscope sensor measurements. Simulation and test results show expected 1-sigma accuracies of 12 arcs and 37 arcs for about- and cross-boresight rotations of the platform, respectively, and average latency times of 6 ms.