Deep Learning-Based Hypersonic Vehicle Motion Behavior Recognition
LIN Zhaochen1， ZHANG Xinran1， LIU Ziyang1， HE Fenghua1， OUYANG Lei2
1. School of Astronautics， Harbin Institute of Technology， Harbin 150001， Heilongjiang， China；
2. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109，China
Abstract：The hypersonic vehicle has the characteristics of large maneuverability, high speed, long-range and strong threat. It has become a critical weapon development in many countries, and the identification of its motion behavior can significantly support defense and interception. In this study the hypersonic vehicle motion behavior recognition problem under the complex constraints of a no-fly zone was investigated. First, parametric motion equations that can fully describe the behavioral patterns of hypersonic vehicles were developed by analyzing the motion characteristics of hypersonic vehicles， and the trajectory planning problem under the complex constraints was acquired by optimization. Then, the hypersonic vehicle motion behavior recognition algorithm was designed based on deep learning. Finally, simulation experimental results were achieved and analyzed, presenting the effectiveness and generalization ability of the proposed algorithm.
