Star-Identification System Based on Polygon Recognition

Author:

Ramos-Alcaraz Gustavo E.1ORCID,Alonso-Arévalo Miguel A.1ORCID,Nuñez-Alfonso Juan M.2

Affiliation:

1. Department of Electronics and Telecommunications, CICESE Research Center, Ensenada 22860, Mexico

2. UNAM Institute of Astronomy, Ensenada Campus, Ensenada 22860, Mexico

Abstract

Accurate attitude determination is crucial for satellites and spacecraft. Among attitude determination devices, star sensors are the most accurate. Solving the lost-in-space problem is the most critical function of the star sensor. Our research introduces a novel star-identification system that utilizes a polygon-recognition algorithm to assign a unique complex number to polygons created by stars. This system aims to solve the lost-in-space problem. Our system includes a full solution with a lens, image sensor, processing unit, and algorithm implementation. To test the system’s performance, we analyzed 100 night sky images that resembled what a real star sensor in orbit would experience. We used a k-d tree algorithm to accelerate the search in the star catalog of complex numbers. We implemented various verification methods, including internal polygon verification and a voting mechanism, to ensure the system’s reliability. We obtained the star database used as a reference from the Gaia DR2 catalog, which we filtered, to eliminate irrelevant stars, and which we arranged by apparent magnitude. Despite manually introducing up to three false stars, the system successfully identified at least one star in 97% of the analyzed images.

Funder

Mexican National Council on Science and Technology (CONACYT) of Mexico

Publisher

MDPI AG

Subject

Aerospace Engineering

Reference46 articles.

1. Lavender, A. (2023, June 28). Satellites Orbiting the Earth in 2022. Available online: https://www.pixalytics.com/satellites-in-2022/.

2. UNOOSA (2023, June 28). United Nations Office for Outer Space Affairs, Online Index of Objects Launched into Outer Space. Available online: https://www.unoosa.org/oosa/osoindex/search-ng.jspx?lf_id=.

3. Kulu, E. (2023, June 28). World’s Largest Database of Nanosatellites, over 3600 Nanosats and CubeSats. Available online: https://www.nanosats.eu.

4. Spacecraft Attitude and Angular Rate Tracking using Reaction Wheels and Magnetorquers;Gravdahl;IFAC-PapersOnLine,2020

5. Pattern recognition of star constellations for spacecraft applications;Liebe;IEEE Aerosp. Electron. Syst. Mag.,1992

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