Event-based Star Tracking under Spacecraft Jitter: the e-STURT Dataset
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866909615168421888 |
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| author | Bagchi, Samya Anastasiou, Peter Tetlow, Matthew Chin, Tat-Jun Latif, Yasir |
| author_facet | Bagchi, Samya Anastasiou, Peter Tetlow, Matthew Chin, Tat-Jun Latif, Yasir |
| contents | Jitter degrades a spacecraft's fine-pointing ability required for optical communication, earth observation, and space domain awareness. Development of jitter estimation and compensation algorithms requires high-fidelity sensor observations representative of on-board jitter. In this work, we present the Event-based Star Tracking Under Jitter (e-STURT) dataset -- the first event camera based dataset of star observations under controlled jitter conditions. Specialized hardware employed for the dataset emulates an event-camera undergoing on-board jitter. While the event camera provides asynchronous, high temporal resolution star observations, systematic and repeatable jitter is introduced using a micrometer accurate piezoelectric actuator. Various jitter sources are simulated using distinct frequency bands and utilizing both axes of motion. Ground-truth jitter is captured in hardware from the piezoelectric actuator. The resulting dataset consists of 200 sequences and is made publicly available. This work highlights the dataset generation process, technical challenges and the resulting limitations. To serve as a baseline, we propose a high-frequency jitter estimation algorithm that operates directly on the event stream. The e-STURT dataset will enable the development of jitter aware algorithms for mission critical event-based space sensing applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_12588 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Event-based Star Tracking under Spacecraft Jitter: the e-STURT Dataset Bagchi, Samya Anastasiou, Peter Tetlow, Matthew Chin, Tat-Jun Latif, Yasir Computer Vision and Pattern Recognition Signal Processing Jitter degrades a spacecraft's fine-pointing ability required for optical communication, earth observation, and space domain awareness. Development of jitter estimation and compensation algorithms requires high-fidelity sensor observations representative of on-board jitter. In this work, we present the Event-based Star Tracking Under Jitter (e-STURT) dataset -- the first event camera based dataset of star observations under controlled jitter conditions. Specialized hardware employed for the dataset emulates an event-camera undergoing on-board jitter. While the event camera provides asynchronous, high temporal resolution star observations, systematic and repeatable jitter is introduced using a micrometer accurate piezoelectric actuator. Various jitter sources are simulated using distinct frequency bands and utilizing both axes of motion. Ground-truth jitter is captured in hardware from the piezoelectric actuator. The resulting dataset consists of 200 sequences and is made publicly available. This work highlights the dataset generation process, technical challenges and the resulting limitations. To serve as a baseline, we propose a high-frequency jitter estimation algorithm that operates directly on the event stream. The e-STURT dataset will enable the development of jitter aware algorithms for mission critical event-based space sensing applications. |
| title | Event-based Star Tracking under Spacecraft Jitter: the e-STURT Dataset |
| topic | Computer Vision and Pattern Recognition Signal Processing |
| url | https://arxiv.org/abs/2505.12588 |