摘要
针对约束条件下传感器优化布站问题,提出了一种基于遗传粒子群算法(GA-PSO)的多传感器优化布站方法。首先网格化战场地理环境,依据战场地理环境和战术条件建立布站约束矩阵;然后考虑任务需求,建立基于探测覆盖率的目标优化函数;最后采用遗传粒子群算法求解传感器最优布站位置。仿真实验验证了所提方法的有效性和合理性。
To solve the problem of sensor optimal deployment in the constrained conditions,a multisensor optimal deployment method is proposed based on genetic algorithm particle swarm optimization( GA-PSO). The method firstly meshes the battlefield geography environment and establishes the constraint matrix of deployment according to the battlefield geography environment and tactical conditions.Then,the objective optimization function based on detection coverage is established. Finally,the GAPSO is used to solve the optimal position of the sensor. The simulation verifies the effectiveness and rationality of the proposed method.
作者
俞宙
单甘霖
段修生
YU Zhou;SHAN Gan-lin;DUAN Xiu-sheng(Army Engineering University,Shijiangzhuang Compus,Hehei Shijiazhuang 050003,China;Shijiazhuang Tiedao University,Hebei Shijiazhuang 050003,China)
出处
《现代防御技术》
2018年第6期94-101,共8页
Modern Defence Technology
关键词
协同探测
区域覆盖
战场地理
战术条件
多传感器
优化布站
遗传粒子群算法
collaborative detection
area coverage
battlefield geography
tactical conditions
multisensor
optimal deployment
genetic algorithm particle swarm optimization(GA-PSO)
