/UAVOpticalTarget_public

UAV target positioning integrating multi-dimensional attitude adaptive sensing.

Primary LanguagePython

LING Zhicheng,LEI Zhongkui,HUANG Daqing,et al.UAV target positioning integrating multi-dimensional attitude adaptive sensing[J].Optics and Precision Engineering,2024,32(14):2272-2285.

DOI: 10.37188/OPE.20243214.2272

Aiming to address the challenge of identifying and eliminating systematic errors in various atti⁃tudes during target positioning of UAV optoelectronic reconnaissance platforms, a study was conducted on a target positioning system that integrates multi-dimensional attitude adaptive sensing algorithms. This pa⁃per presented a comprehensive target position calculation model that was based on the principles of target positioning. It utilized the optoelectronic reconnaissance platform's locking and tracking capabilities to perform multiple measurements of the cooperative target point. Furthermore, it analyzed the differentiated representations of the multi-dimensional attitude systematic error offset from the positioning results. Based on the principles of deep neural networks, the proposed model aimed to perform adaptive estimation and re⁃verse compensation of systematic errors in a multi-task temporal feature extraction framework. Results of experiments indicate that when UAV operates at an altitude of 4000 m, the system is able to mitigate 77% of systematic errors. It successfully reduces the target positioning error from 103 m to 19 m, result⁃ing in an 81% increase in overall positioning accuracy. Consequently, this system enables high-precision positioning of UAV targets.