Vision-Based Continuous Robust LOS Angle Measurement with Seamless Parameter Adaptation for Approaching a Spacecraft Component

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Authors: Fei Xie, Ling Wang, B. Xinhua Wang, Jingwen Zheng, Xiang Zhang
Cited by: 0
References: 24

Abstract

The component-level line of sight (LOS) angle measurement of spacecraft is much desired during space rendezvous, especially for component-related operations, such as component status evaluation, component repair, etc. However, most existing methods rarely consider the component approaching scenario where a continuous, stable, real-time LOS angle measurement method for the component of interest is needed. In this paper, a continuous robust component-level LOS angle measurement method with high computational efficiency applicable to the approach of the key component is proposed. Firstly, an adaptive gamma correction method is introduced to enhance the image quality in complex and variable lighting environments. Secondly, optimized thresholding that exploits information entropy is proposed to identify the pixels that are supposed to be the target from the background. Region detection is subsequently performed to segment the target region into suspected component regions, which can account for target changes during the approach by seamless parameter adaptation. Then, solar panels are recognized and accurately segmented based on the prior knowledge of their spatial relationship with other components and unique shape features. Finally, the centers of solar panels are localized and their LOS angles are calculated. Extensive experiments are conducted to demonstrate the performance of our proposed method, including the verification of the superiority of the solar panel recognition and segmentation method using both simulated images generated by an image simulator and actual images taken by a camera in a dark-room considering the actual lighting in space, and the validation of the ability of supporting real-time component-level LOS angle measurement by ground semi-physical experiments with a guidance, navigation and control (GNC) system incorporated to simulate an on-line dynamic approach.

Fields of Study & Subjects

Space Satellite Systems and Control Spacecraft Dynamics and Control Advanced Neural Network Applications

Publication details

Journal / source
Sensors
Volume
26
Issue
5
Pages
1608–1608
Publication date
4 March 2026
Language
EN