• Electronics Optics & Control
  • Vol. 30, Issue 12, 93 (2023)
CHENG Qing, LI Yiheng, and LU Hede
Author Affiliations
  • [in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2023.12.015 Cite this Article
    CHENG Qing, LI Yiheng, LU Hede. UAV-Aided Localization Based on Extended Kalman Filtering[J]. Electronics Optics & Control, 2023, 30(12): 93 Copy Citation Text show less

    Abstract

    Faced with complex electromagnetic environment of urban low-altitude areas,GNSS signals are prone to be interfered during UAV operation,leading to inaccurate positioning.In order to improve the accuracy of UAV positioning,a data fusion method based on extended Kalman filtering is proposed.Based on the inertial navigation system,the fusion with 3D positioning based on 5G signals is conducted,and inertial navigation errors are corrected by using the fused data.The software simulation shows that the attitude error and the position error are limited within a certain range in the absence of effective GNSS signals,and the accuracy of UAV positioning is improved.The average position error under sight distance is 16.6 cm,and the positioning accuracy is improved by 49.7% compared with that before fusion.The UAV’s ability to have high positioning accuracy for a long duration is realized,and the method has certain engineering practicality.
    CHENG Qing, LI Yiheng, LU Hede. UAV-Aided Localization Based on Extended Kalman Filtering[J]. Electronics Optics & Control, 2023, 30(12): 93
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