Research on Intention Recognition of Air Target Based on Machine Learning

With the evolution and enhancement of air combat forces in modern warfare, accurate recognition of the combat intentions of air targets plays a vital role in battlefield situation assessment and command decision-making. This paper comprehensively sorts out and deeply analyzes the research on air target intention recognition through a systematic literature review method. The article first introduces the relevant concepts of intention recognition, summarizes the application of the two key elements of air target intention recognition, and explores its basic problems in the military field. Then, the research progress of traditional and machine learning-based intention recognition approaches is summarized in chronological order, outlining the main progress and shortcomings of current research, besides, the performance of various methods is compared. Since deep learning technology has shown great application potential in the field of intention recognition in complex battlefields, this paper constructs an intention recognition framework using deep learning methods. Finally, the future research direction of air target intention recognition is prospected, and targeted research suggestions are put forward.