Abstract 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 50 Hz using a prototype built from commercial-off-the-shelf components. Additional results and video demos can be found in the accompanying repository (https://www.yasirlatif.info/ultrafinestabilisation) online.


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    Title :

    High Frequency, High Accuracy Pointing Onboard Nanosats Using Neuromorphic Event Sensing and Piezoelectric Actuation


    Additional title:

    J Astronaut Sci


    Contributors:


    Publication date :

    2025-03-07




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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