Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Adaptive dynamic adjustment star identification threshold estimation for a terrestrial star tracker

Not Accessible

Your library or personal account may give you access

Abstract

As the criterion to determine whether stars are identified, the star image identification matching threshold is an important parameter in terrestrial star trackers. It not only determines the identification success rate, but also affects the redundant matching quantity and identification efficiency. This paper focuses on the problem that the identification efficiency of terrestrial star trackers is restricted by inappropriate matching thresholds and presents an adaptive dynamic adjustment star identification threshold model. Compared to the existing matching threshold, the presented model clarifies the transformation of observation star angular distance errors and dynamically estimates the corresponding identification threshold as the variation of observation angular distances and attitudes. Therefore, we believe it completes the star identification with an excellent redundant matching quantity and identification efficiency. Numerical simulation and night sky experimental results showed that the identification efficiency was improved by more than 46.54% and 22.61%, respectively, while the identification success rate remained at 100%.

© 2022 Optica Publishing Group

Full Article  |  PDF Article
More Like This
Observation angular distance error modeling and matching threshold optimization for terrestrial star tracker

Zhen Wang, Jie Jiang, and Guangjun Zhang
Opt. Express 27(23) 33518-33536 (2019)

Star spot location estimation using Kalman filter for star tracker

Hai-bo Liu, Jian-kun Yang, Jiong-qi Wang, Ji-chun Tan, and Xiu-jian Li
Appl. Opt. 50(12) 1735-1744 (2011)

Robust and adaptive star identification algorithm based on linear assignment for multiple large field of view visual imaging systems

Guangyi Dai, Qilin Liu, Lei Deng, Peng Sun, Bixi Yan, Jun Wang, and Mingli Dong
Appl. Opt. 63(12) 3192-3201 (2024)

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (14)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Tables (3)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (26)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.