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Relative Positioning Method for UAVs Based on Multi-Source Information Fusion

He Song, Shaolin Hu, Qiliang Guo, Wenqiang Jiang and Ana C. Teodoro

Mathematical Problems in Engineering, 2022, vol. 2022, 1-15

Abstract: To improve the accuracy and reliability of the relative positioning for unmanned aerial vehicles (UAVs), a relative positioning method based on multi-source information fusion is proposed. An integrated positioning scheme is constructed by the Beidou Navigation Satellite System (BDS) receivers, Global Positioning System (GPS) receivers, Vision-Based Navigation System (VisNav), and Inertial Navigation System (INS). The BDS pseudorange relative difference equation, the GPS relative difference equation, the relative line-of-sight vector equation, and the INS measurement equation are established, respectively. The least squared (LS) method is used to realize information fusion, and the Gauss-Newton method is used to iteratively solve the relative position results. Finally, numerical simulation and result analysis are conducted with different sensor configurations. Simulation results show that BDS/INS/GPS/VisNav relative positioning result is obviously better than that of INS/GPS, INS/VisNav, and INS/GPS/VisNav, and the proposed method reduces the relative positioning errors and has a higher accuracy and excellent robustness. The research result is suitable for application scenarios with high navigation accuracy requirement such as AAR and intelligent swarm formation control.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:3755861

DOI: 10.1155/2022/3755861

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