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An On-Orbit Star Tracker Benchmark for Resident Space Object Detection and Attitude Estimation
Vithurshan Suthakar1, Perushan Kunalakantha2, Regina S K Lee2
1Department of Earth and Space Science, York University, Toronto, ON, M3J 1P3, Canada. vithurs@my.yorku.ca.
Scientific Data
|June 25, 2026
Summary
This study introduces a new dataset of space object imagery for enhanced space situational awareness. The data supports improved detection, tracking, and attitude estimation for spacecraft navigation.
Area of Science:
- Space Science
- Astrodynamics
- Optical Remote Sensing
Background:
- Space situational awareness (SSA) relies heavily on optical observations.
- Existing datasets often lack on-orbit, wide field-of-view imagery with joint space object and star labels.
Purpose of the Study:
- To present a novel dataset of near-infrared images for SSA.
- To provide a valuable resource for space object detection, tracking, and attitude estimation.
Main Methods:
- Acquired near-infrared images using the Fast Auroral Imager on the CASSIOPE spacecraft (Jan-Aug 2023).
- Collected 1,378 frames with astrometrically calibrated stars and 4,237 verified resident space object instances.
- Included spacecraft ephemeris, attitude, and image quality metrics; described calibration and annotation pipeline.
Main Results:
- Validated pointing stability, astrometric accuracy, and annotation reliability.
- Characterized background conditions for the acquired imagery.
- Dataset supports diverse SSA tasks including object detection in star fields and multi-object tracking.
Conclusions:
- The presented dataset is a significant contribution to space situational awareness research.
- It facilitates advancements in on-orbit object detection, tracking, and spacecraft attitude estimation.
- This shared resource is intended to benefit navigation and SSA studies.
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