论文类型：
期刊论文
第一作者：
Ning, Qian
通讯作者：
Chen, BC (reprint author), Dalian Univ Technol, Sch Comp Sci & Technol, Dalian 116024, Peoples R China.
合写作者：
Tao, Guiping,Chen, Bingcai,Lei, Yinjie,Yan, Hua,Zhao, Chengping
发表时间：
2019-08-01
发表刊物：
PHYSICAL COMMUNICATION
收录刊物：
SCIE、EI
文献类型：
J
卷号：
35
ISSN号：
1874-4907
关键字：
Collaborative mission planning; Trajectory planning; Survival state;
Markov model; Meta-heuristic search algorithms
摘要：
As the environment of the battlefield is increasingly complex, single UAV (Unmanned Aerial Vehicle) has trouble in carrying out missions, which requires the cooperation of multiple UAVs. However, search space is very large and search targets are distributed sparsely, and making mission planning and route planning simultaneously is also an NP (Non-Deterministic Polynomial Problems) problem, which makes it extremely difficult in mission planning. Recently, meta-heuristic search algorithms widely used in multi-UAVs collaborative mission planning are difficult to find reliable initial solutions and limit the convergence speed. Aiming at this problem, to take plenty of constraints and performance planning targets in multi-UAV cooperative mission planning problems into full consideration. This paper proposes a two-layer mission planning model based on the simulated annealing algorithm and tabu search algorithm, which solves multi-objectives, Multi-aircraft mission planning problems. This paper combined the five-state Markov chain model with the mission planning model to determine the optimal mission planning scheme by judging the survival state probability of the flight platform. Finally, the simulation results show that this method can greatly improve the survivability of the drone while ensuring optimal mission planning. (C) 2019 Elsevier B.V. All rights reserved.
是否译文：
否
