Abstract
With the rapid development of artificial intelligence technology, the form of warfare is undergoing profound changes, intelligent, unmanned, networked warfare has gradually become the mainstream form of warfare. As the core of artificial intelligence, machine learning has achieved great success in the fields of computer vision, natural language processing, and recommendation systems. For current UAV combat missions, machine learning also has great application potential. In this study, based on the traction of UAV combat requirements, we focus on the research and analysis of the application of machine learning in UAV situation awareness and autonomous decision making. With its powerful data analysis advantages, machine learning can assist UAV in extracting key information from massive battlefield information, and quickly realize the conversion from data information to decision making to improve the speed of battlefield reaction, planning and decision making. Therefore, the application of machine learning to situation awareness fusion and decision-making is of great significance and worthy of in-depth research and exploration.
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Ren, Y., Cao, XQ., Guo, YN., Peng, KC., Xiao, CH., Tian, WL. (2022). Application of Machine Learning in UAV Combat. In: Wu, M., Niu, Y., Gu, M., Cheng, J. (eds) Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021). ICAUS 2021. Lecture Notes in Electrical Engineering, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-16-9492-9_290
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