As satellites become smaller, the ability to maintain stable pointing decreases as external forces acting on the satellite come into play. At the same time, reaction wheels used in the attitude determination and control system (ADCS) introduce high frequency jitter which can disrupt pointing stability. For space domain awareness (SDA) tasks that track objects tens of thousands of kilometres away, the pointing accuracy offered by current nanosats, typically in the range of 10 to 100 arcseconds, is not sufficient. In this work, we develop a novel payload that utilises a neuromorphic event sensor (for high frequency and highly accurate relative attitude estimation) paired in a closed loop with a piezoelectric stage (for active attitude corrections) to provide highly stable sensor-specific pointing. Event sensors are especially suited for space applications due to their desirable characteristics of low power consumption, asynchronous operation, and high dynamic range. We use the event sensor to first estimate a reference background star field from which instantaneous relative attitude is estimated at high frequency. The piezoelectric stage works in a closed control loop with the event sensor to perform attitude corrections based on the discrepancy between the current and desired attitude. Results in a controlled setting show that we can achieve a pointing accuracy in the range of 1-5 arcseconds using our novel payload at an operating frequency of up to 50Hz using a prototype built from commercial-off-the-shelf components. Further details can be found at https://ylatif.github.io/ultrafinestabilisation
翻译:随着卫星体积不断减小,其维持稳定指向的能力因外部作用力的影响而下降。同时,姿态确定与控制系统(ADCS)中使用的反作用轮会引入高频抖动,破坏指向稳定性。对于追踪数万公里外物体的空间态势感知(SDA)任务而言,当前纳米卫星通常10至100角秒的指向精度仍显不足。本研究开发了一种新型有效载荷,通过闭环耦合神经形态事件传感器(用于高频率、高精度相对姿态估计)与压电平台(用于主动姿态校正),实现高度稳定的传感器特定指向。事件传感器因其低功耗、异步运行和高动态范围等优异特性,特别适用于空间应用。我们首先利用事件传感器估计参考背景星场,并从中以高频率解算瞬时相对姿态。压电平台与事件传感器构成闭环控制回路,根据当前姿态与期望姿态的偏差进行姿态校正。在受控环境下的实验结果表明,采用商用货架部件构建的原型系统,可在高达50Hz的工作频率下实现1-5角秒的指向精度。详细信息见https://ylatif.github.io/ultrafinestabilisation