Abstract
Unmanned aerial vehicle (UAV) is an unmanned aircraft remotely controlled by radio, which is widely used in reconnaissance. However, during the operation of UAV, the positioning signal is easily disturbed by noise, which leads to low separation accuracy and poor positioning effect of fixed wing UAV. To this end, a fixed wing UAV positioning signal separation algorithm based on artificial intelligence is proposed. The fixed-wing UAV positioning signal denoising algorithm is constructed by collecting the feature information of fixed-wing UAV, and the denoising of fixed-wing UAV positioning signal is completed. In order to reduce the signal separation error and realize the fixed wing UAV positioning signal separation, signal separation is processed according to the positioning signal algorithm. Experimental results show that the proposed algorithm can effectively separate the UAV location signal from the noise, and has high accuracy and good location effect under serious multipath interference.
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National Natural Science Foundation of China Major Project (61890964).
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zou, Z., Wei, Z. (2023). Separation Algorithm of Fixed Wing UAV Positioning Signal Based on AI. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-031-28787-9_23
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DOI: https://doi.org/10.1007/978-3-031-28787-9_23
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