Air-bearing platforms for simulating the rotational dynamics of satellites require highly precise ground truth systems. Unfortunately, commercial motion capture systems used for this scope are complex and expensive. This paper shows a novel and versatile method to compute the attitude of rotational air-bearing platforms using a monocular camera and sets of fiducial markers. The work proposes a geometry-based iterative algorithm that is significantly more accurate than other literature methods that involve the solution of the Perspective-n-Point problem. Additionally, auto-calibration procedures to perform a preliminary estimation of the system parameters are shown. The developed methodology is deployed onto a Raspberry Pi 4 micro-computer and tested with a set of LED markers. Data obtained with this setup are compared against computer simulations of the same system to understand and validate the attitude estimation performances. Simulation results show expected 1-sigma accuracies in the order of $\sim$ 12 arcsec and $\sim$ 37 arcsec for about- and cross-boresight rotations of the platform, and average latency times of 6 ms.

翻译：气浮平台用于模拟卫星旋转动力学时，需要具备高精度的真实参考系统。然而，用于该目的的商用运动捕捉系统结构复杂且成本高昂。本文提出一种新颖且通用的方法，利用单目相机和基准标记集计算旋转气浮平台的姿态。该研究开发了一种基于几何的迭代算法，其精度显著优于现有文献中通过求解透视n点问题的方法。此外，本文还展示了用于系统参数初步估计的自校准流程。所提出的方法在树莓派4微计算机上部署，并通过一组LED标记进行测试。将实验数据与相同系统的计算机仿真结果进行对比，以验证姿态估计性能。仿真结果表明，平台在沿光轴旋转和跨光轴旋转方向上的1σ精度分别约为12角秒和37角秒，平均延迟时间为6毫秒。