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基于文化鱼群算法的到达时间差定位技术
引用本文:高洪元,于雪梅,赵忠凯.基于文化鱼群算法的到达时间差定位技术[J].计算机工程,2011,37(14):137-139.
作者姓名:高洪元  于雪梅  赵忠凯
作者单位:哈尔滨工程大学信息与通信工程学院,哈尔滨,150001
基金项目:黑龙江省科技攻关计划基金资助项目,中央高校基本科研业务费专项基金资助项目
摘    要:针对到达时间差(TDOA)定位估计中的非线性最优化问题,在鱼群算法中引入文化机制设计基于实数编码的文化鱼群算法,将Chan算法的解作为文化鱼群的一个个体初始位置,并利用文化鱼群算法搜索TDOA定位的最优坐标。仿真结果表明,该技术性能稳定,在鱼群规模较小的情况下能快速鲁棒地找到逼近全局最优点的解,并且具有较快的搜索速度和较高的搜索精度。

关 键 词:到达时间差  无线定位  文化鱼群算法  最大似然估计  Chan算法
收稿时间:2011-02-17

Time Difference of Arrival Location Technology Based on Cultural Fish Swarm Algorithm
GAO Hong-yuan,YU Xue-mei,ZHAO Zhong-kai.Time Difference of Arrival Location Technology Based on Cultural Fish Swarm Algorithm[J].Computer Engineering,2011,37(14):137-139.
Authors:GAO Hong-yuan  YU Xue-mei  ZHAO Zhong-kai
Affiliation:(College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China)
Abstract:Aiming at the nonlinear optimization problem of Time Difference of Arrival(TDOA) location, this paper proposes the Cultural Fish Swarm(CFS) algorithm of real coding which introduces cultural operator to artificial fish swarm algorithm. By adding the solution of Chan algorithm into initial population of CFS algorithm, the CFS method can search the optimal coordinates of TDOA location fast. Simulation results show that the technology has stable performance, if the population size is small, the technology is robust and can find the coordinates of optimization, and it has higher search speed and search precision.
Keywords:Time Difference of Arrival(TDOA)  wireless location  Cultural Fish Swarm(CFS) algorithm  maximum likelihood estimation  Chanalgorithm
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