融合PSO和Powell的雷达组网反隐身部署优化算法
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PSO Powell Integrated Algorithm for Anti stealth Deployment Optimization of N etted Radar
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    摘要:

    针对多雷达组网探测隐身目标的部署优化问题, 根据雷达探测隐身目标的简化模型,在目标运动轨迹确定的情况下,设计了反隐身部署优化 两级指标。由于雷达网部署为具有多个可行解的多目标优化问题,提出了一种融合粒子群(P article swarm optimization, PSO)和 鲍威尔(Powell)搜索法的分层搜索算法。首先采用粒子群优化算法得到全局和局部最优解, 然后采用 鲍威尔算法进一步搜索得到部署方案。仿真结果表明,提出的算法充分结合了粒子群算法的 全局搜索能力和鲍威尔算法的局部搜索能力,与仅采用粒子群算法相比,得到的部署方案在 保证责任区覆盖的前提下,有效提高了雷达网对隐身目标的探测概率,增加了对隐身目标的 预警距离。

    Abstract:

    To sol ve the deployment optimization problem for detecting stealth target based on net ted radar, two level anti stealth optimization indexes are presented according t o the simplified model of detecting stealth target using single radar when the o bject trajectory is fixed. Since netted radar deployment is a mult i objective optimization problem with multiple solutions, the hierarchical sear c h algorithm integrated particle swarm optimization (PSO) with Powell is propose d. Firstly PSO algorithm is used to obtain global and local optimal solution. Th en the Powell algorithm is used to search the final deployment solution. Si mul ation results demonstrate that the proposed algorithm combines the advantages o f PSO′s global search ability and Powell′s local search ability. The deploymen t solution using the proposed algorithm compared with the PSO algorithm i mproves the detection probability of stealth target effectively, and increases t he warning distance, under the premise that responsible cover area does not decr ease.

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谷雨;张辰璐;李汉文;彭冬亮.融合PSO和Powell的雷达组网反隐身部署优化算法[J].数据采集与处理,2016,31(3):525-531

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  • 在线发布日期: 2016-06-24