Dynamic measurement of a long‐distance moving object using multi‐binocular high‐speed videogrammetry with adaptive‐weighting bundle adjustment

Author:

Tong Xiaohua12ORCID,Gao Yi1,Ye Zhen1ORCID,Xie Huan12,Chen Peng12,Shi Haibo1,Liu Ziqi1,Liu Xianglei3,Xu Yusheng1,Huang Rong1,Liu Shijie1

Affiliation:

1. College of Surveying and Geo‐Informatics, Tongji University Shanghai China

2. The State Key Laboratory for Disaster Reduction in Civil Engineering Tongji University Shanghai China

3. Key Laboratory for Urban Geomatics of National Administration of Surveying, Mapping and Geoinformation Beijing University of Civil Engineering and Architecture Beijing China

Abstract

AbstractThe dynamic measurement of position and attitude information of a long‐distance moving object is a common demand in ground testing of aerospace engineering. Due to the movement from far to near and the limitations of camera resolution, it is necessary to use multi‐binocular cameras for segmented observation at different distances. However, achieving accurate and continuous position and attitude estimation is a challenging task. Therefore, this paper proposes a dynamic monitoring technique for long‐distance movement based on a multi‐binocular videogrammetric system. Aiming to solve the problem that the scale in images changes constantly during the moving process, a scale‐adaptive tracking method of circular targets is presented. Bundle adjustment (BA) with joint segments using an adaptive‐weighting least‐squares strategy is developed to enhance the measurement accuracy. The feasibility and reliability of the proposed technique are validated by a ground testing of relative measurement for spacecraft rendezvous and docking. The experimental results indicate that the proposed technique can obtain the actual motion state of the moving object, with a positioning accuracy of 3.2 mm (root mean square error), which can provide a reliable third‐party verification for on‐orbit measurement systems in ground testing. Compared with the results of BA with individual segments and vision measurement software PhotoModeler, the accuracy is improved by 45% and 30%, respectively.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shanghai Municipality

Fundamental Research Funds for the Central Universities

Publisher

Wiley

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