Observation-Driven Multiple UAV Coordinated Standoff Target Tracking Based on Model Predictive Control

作     者：Shun Sun Yu Liu Shaojun Guo Gang Li Xiaohu Yuan Shun Sun;Yu Liu;Shaojun Guo;Gang Li;Xiaohu Yuan

作者机构：Department of Control Science and TechnologyNaval Aviation UniversityYantai 264001China Department of Electronic EngineeringTsinghua UniversityBeijing 100084China National Institute of Defense Technology InnovationAcademy of Military Sciences PLABeijing 100091China Department of AutomationTsinghua UniversityBeijing 100084China 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2022年第27卷第6期

页      面：948-963页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 082503[工学-航空宇航制造工程] 0714[理学-统计学（可授理学、经济学学位）] 0802[工学-机械工程] 0835[工学-软件工程] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程] 080201[工学-机械制造及其自动化] 

基　　金：supported in part by the National Natural Science Foundation of China(Nos.62022092 and 61790550) 

主　　题：coordinated tracking standoff tracking observation-driven Model Predictive Control(MPC) multiple UAVs Fisher Information Matrix(FIM) 

摘      要：An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a *** acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized *** facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff ***,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its *** experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.