Collaborative Defense with Multiple USVs and UAVs Based on Swarm Intelligence

作     者：WU Xing LIU Yuan XIE Shaorong GUO Yike 武星;刘远;谢少荣;郭毅可

作者机构：School of Computer Engineering and ScienceShanghai UniversityShanghai 200444China Shanghai Institute for Advanced Communication and Data ScienceShanghai 200444China Department of ComputingImperial College LondonLondon SW72AZUnited Kingdom 

出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)

年 卷 期：2020年第25卷第1期

页      面：51-56页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：the National Natural Science Foundation of China(No.61625304) 

主　　题：collaborative defense mission assignment path planning unmanned surface vehicles(USVs) unmanned aerial vehicles(UAVs) 

摘      要：Modern defense systems are developing towards *** and automation,which include the collaborative defense system on the sea between multiple unmanned surface vehicles(USVs)and unmanned aerial vehicles(UAVs).UAVs can fly in high altitude and collect marine environment information on ***,UAVs can plan defense paths for USVs to intercept intruders with full-assignment or reassignment strategies aiming at maximum overall ***,we propose dynamic overlay reconnaissance algor计hm based on genetic idea(GI-DORA)to solve the problem of multi-UAV multi-station ***,we develop continuous particle swarm optimization based on obstaele dimension(OD-CPSO)to optimize defense path of USVs to intercept *** addition,under the designed defense constraints,we propose dispersed particle swarm optimization based on mutation and crossover(MC-DPSO)and real-time batch assignment algorithm(RTBA)in emergency for formulating combat defense mission assignment strategy in different ***,we illus trate the feasibility and effectiveness of the proposed met hods.