Active switching multiple model method for tracking a noncooperative gliding flight vehicle

• 作 者: Tianyu ZHENG Yu YAO Fenghua HE Denggao JI Xinran ZHANG
• 机 构: School of Astronautics, Harbin Institute of Technology, Harbin 150001, China;Beijing Institute of Ne
• 出 处: 中国科学：信息科学（英文版）
• 发表日期: 2020年9期
• 关键词: gliding flight vehicle target tracking multiple model estimation and fusion moti

The study investigates the trajectory estimation problem of a noncooperative gliding flight vehicle with complex and atypical maneuvers.An active switching multiple model (ASMM) method is proposed.This method employs a motion behavior model set (MBMS),a motion behavior recognition algorithm,and an active switching estimation and fusion algorithm.First,a recognizable MBMS,which can capture all the motion behaviors of a gliding flight vehicle,is established.Then,a motion behavior recognition algorithm based on recurrent neural networks (RNNs) is developed to obtain the current probability of each motion behavior.Then,an active switching estimation and fusion algorithm is proposed,in which the adopted models are actively chosen at each time instant according to a model selection strategy.Last,the proposed ASMM method is applied to a noncooperative gliding flight vehicle.The simulation results show that the proposed method has higher estimation precision and better dynamic performance.