受限通信范围下海上目标的多无人机协同搜索算法  

Cooperative search algorithm of multi-UAV for sea targets in limited communication range

作　　者：王可铮 周兴莲 林梦婷 李彬 WANG Kezheng;ZHOU Xinglian;LIN Mengting;LI Bin(Solutions&Services Group,Lenovo,Chengdu 610041,China;School of Aeronautics and Astronautics,Sichuan University,Chengdu 610000,China)

机构地区：[1]联想集团方案服务业务集团,四川成都610041 [2]四川大学空天科学与工程学院,四川成都610000

出　　处：《传感器与微系统》2022年第12期143-146,157,共5页Transducer and Microsystem Technologies

基　　金：国防基础科研项目(JCKY2021204B051)。

摘　　要：针对低动态的海上舰船目标展开多无人机(UAV)协同搜索问题研究,考虑战场环境下无人机通信范围受限,实现了动态环境下的多无人机协同搜索航迹规划。首先,将任务区域栅格化,根据先验信息得到初始搜索概率地图;其次,综合考虑多目标与多约束,将协同搜索问题建模为带约束的优化问题;最后,在分布式模型预测控制(DMPC)框架下,采用冻结策略,将上述优化问题进行分布式求解,并根据建立的地图更新策略和实时搜索信息对地图进行更新。仿真结果表明:所提出的分布式模型预测控制协同搜索算法,相比于传统的平行搜索算法,能够有效应对通信范围受限问题,并高效完成目标搜索任务。Aiming at research of multi-UAV cooperative search problem for maritime ship targets with low dynamic characteristics is carried out, considering the communication range of UAV is limited in the battlefield environment, the multi-UAV cooperative search trajectory planning in dynamic environment is realized.Firstly, the task area is rasterized to obtain the initial search probability map according to the prior information.Secondly, the cooperative search problem is modeled as an optimization problem with constraints by comprehensively considering multiple objectives and multiple constraints.Finally, the above optimization problem is solved in a distributed manner using the frozen strategy under the framework of distributed model predictive control(DMPC).And the map is updated according to the established map update strategy and real-time search information.The simulation results show that the proposed DMPC cooperative search algorithm can effectively cope with the problem of communication range constraint and efficiently accomplish the target search task compared with the traditional parallel search algorithm.

关 键 词：多无人机 协同搜索 分布式模型预测控制 

分 类 号：V249.1[航空宇航科学与技术—飞行器设计] TP391[自动化与计算机技术—计算机应用技术]