摘要
针对实际战场对多目标跟踪有决策时效性和具体精度需求的问题,提出一种稳定高效有跟踪精度保证的传感器管理算法。算法充分利用满足多目标精度的解往往不止一个的特点,建立了新颖的传感器优化管理模型,并利用改进的二进制粒子群算法进行求解。求解算法采用了约束满足的初始化方法、V型转换函数的位置更新规则和随迭代次数自适应调整的速度更新规则。仿真结果表明,该算法与传统算法相比拥有更快的收敛速度,能有效避免局部最优,保证实战场景中对目标有稳定精度的跟踪。
Considering the requirement of decision-making timeliness and certain accuracy in the sensor resource assignment, a stable sensor management algorithm ensuring tracking accuracy is pro- posed. The method makes the best of the characteristic that there usually exist more than one solu- tion of the problem, and establishes the optimization modle. Besides, an improved binai7 particle swarm optimization（IBPSO） is proposed to solve the model, which is designed via constraint satis- faction population initialization method, particle position updating rules with V-shaped transter func- tion, and self-adapted velocity updating rules. The simulation results show that compared with tradi- tional algorithms, the proposed one runs with a faster speed, avoids the local optimum and provides the stable accuracy required. So the proposed algorithm has a strong adaptability for the sensor man- agement problem in actual combat scene.
作者
方德亮
冉晓旻
张静
王超
FANG Deliang,RAN Xiaomin,ZHANG Jing,WANG Chao(Information Engineering University, Zhengzhou 450001 ＂ China)
出处
《信息工程大学学报》
2018年第1期15-19,共5页
Journal of Information Engineering University
基金
国家科技重大专项资助项目(2014ZX03006003)
关键词
!协方差控制
传感器管理
目标跟踪
二进制粒子群算法
covariance control
sensor management
target tracking
binary particle swarm optimi-zation
