A Rotation-Invariant Additive Vector Sequence Based Star Pattern Recognition
| Autor: | Deval Mehta, Shoushun Chen, Kay Soon Low |
|---|---|
| Přispěvatelé: | School of Electrical and Electronic Engineering |
| Rok vydání: | 2019 |
| Předmět: |
Star pattern recognition
020301 aerospace & aeronautics Computer science Feature extraction Star Identification Aerospace Engineering Astrophysics::Cosmology and Extragalactic Astrophysics 02 engineering and technology Star tracker 0203 mechanical engineering Electrical and electronic engineering [Engineering] Astrophysics::Solar and Stellar Astrophysics Star Pattern Recognition Astrophysics::Earth and Planetary Astrophysics Electrical and Electronic Engineering Invariant (mathematics) Algorithm Astrophysics::Galaxy Astrophysics |
| Zdroj: | IEEE Transactions on Aerospace and Electronic Systems. 55:689-705 |
| ISSN: | 2371-9877 0018-9251 |
| DOI: | 10.1109/taes.2018.2864431 |
| Popis: | A novel star pattern recognition technique for a “Lost-in-space” mode star tracker is presented in this paper. First, the two-dimensional (2-D) vectors connecting the stars are constructed in a rotation-invariant frame. Later, the additive property of 2-D vectors is integrated with the rotation-invariant frame to build a vector sequence for star identification. The proposed technique achieves an identification accuracy of 98.7% and has a run-time of only 12 ms for real-time testing on star images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|