基于混沌鸡群优化的无人机抗多径盲均衡算法  

Chaos Chicken Swarm Optimization-based Blind Equalization Algorithm for Multipath Mitigation of UAVs

作　　者：张然 陈成锴 潘成胜[2] ZHANG Ran;CHEN Chengkai;PAN Chengsheng(College of Information Engineering,Dalian University,Dalian 116622,China;Communication and Network Key Laboratory,Dalian University,Dalian 116622,China)

机构地区：[1]大连大学信息工程学院,辽宁大连116622 [2]大连大学通信与网络重点实验室,辽宁大连116622

出　　处：《火力与指挥控制》2022年第7期26-31,共6页Fire Control & Command Control

基　　金：装发部领域基金一般资助项目(61403110308)。

摘　　要：针对恒模盲均衡算法在解决无人机抗多径问题时,存在稳态误差较大、收敛速度过慢和易陷入局部早熟的弊端,提出一种基于混沌鸡群优化的无人机抗多径盲均衡算法。在恒模盲均衡算法的基础上,利用混沌理论初始化种群,在鸡群优化算法中引入小鸡的学习系数,并对鸡群的各子群采用混沌变异,以达到全局最优。对该算法进行了实验验证,结果表明,改进算法不仅稳态误差小,收敛速度快,还具备很强的全局收敛能力。Constant modulus blind equalization algorithm(CMA)has the disadvantages of large steady-state errors,slow convergence speed and easy to fall into local precocity in solving the multipath mitigation problem of UAVs(Unmanned Aerial Vehicle).A chaos chicken swarm optimization-based constant modulus blind equalization algorithm(C-CSO-CMA)is proposed.On the basis of CMA,first chaos theory is used to initialize the population.Then chicken learning coefficient is introduced into the chicken swarm optimization algorithm,and chaotic mutation is used for each chicken subgroup to achieve the global optimum.Finally the proposed algorithm is verified by experiments,and the simulation results show that the improved algorithm not only has small steady-state error,fast convergence speed,but also has strong global convergence ability.

关 键 词：鸡群优化算法 混沌理论 盲均衡算法 抗多径 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]