UAV Behavior-Intention Estimation Method Based on 4-D Flight-Trajectory Prediction

Honghai Zhang, Yongjie Yan, Shan Li, Yuxin Hu and Hao Liu
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Honghai Zhang: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Yongjie Yan: State Key Laboratory of Air Traffic Management System and Technology, Nanjing 210007, China
Shan Li: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
Yuxin Hu: State Key Laboratory of Air Traffic Management System and Technology, Nanjing 210007, China
Hao Liu: College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Sustainability, 2021, vol. 13, issue 22, 1-14

Abstract: Aiming at the limitation of the traditional four-dimensional (4-D) trajectory-prediction model of unmanned aerial vehicles (UAV), a 4-D trajectory combined prediction model based on a genetic algorithm is proposed. Based on historical flight data and the UAV motion equation, the model is weighted dynamically by a genetic algorithm, which can predict UAV trajectory and the time of entering the protection zone instantly and accurately. Then, according to the number of areas where the tangent line of the current trajectory point intersects with the collision area, alarm area, alert area, and the time of entering the protection zone, the UAV’s behavior intention can be estimated. The simulation experiments verify the dangerous behaviors of UAV under different danger levels, which provides reference for the subsequent maneuvering strategies.

Keywords: UAV; 4-D flight trajectory; SVR; combined prediction; behavior intention (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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