Event-based Star Tracking under Spacecraft Jitter: the e-STURT Dataset

2025-05-19

AI Summary

High-frequency spacecraft jitter (>100 Hz) severely degrades star tracker accuracy, yet existing event-camera starfield datasets lack controlled, ground-truth jitter annotations—hindering the development of jitter-aware algorithms. To address this, we introduce e-STURT, the first high-fidelity event-camera starfield dataset specifically designed for onboard jitter scenarios. It employs piezoelectric actuators to precisely reproduce multi-band, dual-axis jitter waveforms, enabling hardware-synchronized acquisition of event streams and ground-truth jitter signals. The dataset comprises 200 jitter sequences, each with microsecond-accurate timestamps and precise ground-truth annotations. Furthermore, we propose a novel frequency-domain–temporal joint jitter estimation algorithm operating directly on raw event streams, achieving sub-pixel estimation accuracy under >100 Hz jitter. This work fills a critical gap in high-frequency jitter event-based starfield data and establishes a benchmark dataset and algorithmic foundation for onboard jitter sensing and compensation.

Technology Category

• Intelligent Robots: State Estimation
• Computer Vision: Motion & Tracking
• Reasoning under Uncertainty: Stochastic Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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.

Problem

• Jitter degrades spacecraft fine-pointing for optical communication.
• High-fidelity sensor data needed for jitter compensation algorithms.
• Dataset enables jitter-aware algorithms for event-based space sensing.

Innovation

• Event camera captures high temporal resolution star observations
• Piezoelectric actuator introduces controlled micrometer accurate jitter
• Dataset includes 200 sequences with ground-truth jitter