一种基于改进粒子群算法的机载多传感器任务分配方法 -- 西北工业大学学报,2018,36(4):722-727
论文:2018,Vol:36,Issue(4):722-727
引用本文:
史国庆, 武凡, 张林, 张舒杨, 郭操. 一种基于改进粒子群算法的机载多传感器任务分配方法[J]. 西北工业大学学报
Shi Guoqing, Wu Fan, Zhang Lin, Zhang Shuyang, Guo Cao. An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm[J]. Northwestern polytechnical university

一种基于改进粒子群算法的机载多传感器任务分配方法
史国庆1, 武凡1, 张林1, 张舒杨2, 郭操2
1. 西北工业大学 电子信息学院, 陕西 西安 710072;
2. 沈阳飞机设计研究所, 辽宁 沈阳 110035
摘要:
分析了机载多传感器任务分配问题的特点,建立了机载多传感器任务分配模型。为解决传统粒子群算法存在的局部收敛、收敛较慢等问题,在现有的粒子群算法基础上,调整算法结构与参数,引入方向系数和远离因子来控制粒子远离最劣解的速度和方向,使其在向最优解移动的同时远离最劣解;基于改进后的粒子群算法提出了一种以最大探测概率为目标函数的机载多传感器任务分配方法,并进行了算法仿真。仿真结果表明,算法可以进行有效的任务分配,并能够提升分配效果。
关键词:    任务分配    机载多传感器    改进粒子群算法    探测概率   
An Airborne Multi-Sensor Task Allocation Method Based on Improved Particle Swarm Optimization Algorithm
Shi Guoqing1, Wu Fan1, Zhang Lin1, Zhang Shuyang2, Guo Cao2
1. School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China;
2. Shenyang Aircraft Design & Research Institute, Shenyang 110035, China
Abstract:
The characteristics of airborne multi-sensor task allocation problem are analyzed, and an airborne multi-sensor task allocation model is established. In order to solve the problems of local convergence and slow convergence of the traditional Particle Swarm Optimization (PSO) algorithm, the structure and parameters of the existing Particle Swarm Optimization algorithm are adjusted, and the direction coefficient and far away factor are introduced to control the velocity and direction of the particle far away from the worst solution, so that the particle moves away from the worst solution while moving to the optimal solution. Based on the improved Particle Swarm Optimization algorithm, an airborne multi-sensor task allocation method is proposed using maximum detection probability as objective function, and the algorithm is simulated. The simulation results show that this algorithm can effectively allocate tasks and improve allocation effects.
Key words:    task allocation    airborne multi-sensor    improved particle swarm optimization algorithm    detection probability   
收稿日期: 2017-09-10     修回日期:
DOI:
基金项目: 航空科学基金(ASFC-2017ZC53033)资助
通讯作者:     Email:
作者简介: 史国庆(1974-),西北工业大学副教授、硕士生导师,主要从事航空电子综合化系统仿真、测试研究。
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