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计算机工程 ›› 2008, Vol. 34 ›› Issue (12): 172-174. doi: 10.3969/j.issn.1000-3428.2008.12.061

• 人工智能及识别技术 • 上一篇    下一篇

基于遗传算法和模拟退火算法的TDOA定位技术

侯惠芳1,2,刘素华2,杨铁军2   

  1. (1. 解放军信息工程学院国家数字交换系统工程技术研究中心,郑州 450002;2. 河南工业大学信息科学与工程学院,郑州 450052)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-06-20 发布日期:2008-06-20

TDOA Location Technique Based on Genetic Algorithm and Simulated Annealing Algorithm

HOU Hui-fang1,2, LIU Su-hua2, YANG Tie-jun2   

  1. (1. National Digital Switching System Engineering &Technological R&D Center, PLA Information Engineering College, Zhengzhou 450002; 2. College of Information Science and Engineering, Henan University of Technology, Zhengzhou 450052)
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-06-20 Published:2008-06-20

摘要: 提出一种基于遗传算法与模拟退火算法的TDOA定位估计算法,该算法通过对求解定位坐标计算时的最大似然函数进行求解,实现了利用所有TDOA测量值对移动台的定位估计。该算法采用实数编码,自适应交叉率和变异率实现遗传算法的全局搜索,引入模拟退火的Boltzmann机制,解决遗传算法容易陷入局部最优的问题。实验结果表明,该算法定位精度高、收敛速度快。

关键词: 到达时间差, 遗传算法, 模拟退火算法, 最大似然函数

Abstract: A new TDOA location algorithm based on Genetic Algorithm(GA) and Simulated Annealing(SA) algorithm is proposed. The algorithm utilizing GA and SA algorithm can be applied to all TDOA measures for location by computing the maximum likelihood function of the location coordinate. It achieves global searching by adopting real-code and adaptive crossover and mutation in GA, and solves easy trapping into local optimum value problem of GA by inducting Boltamann mechanism of SA. Numerical simulations show that the algorithm has higher accuracy and rapid convergence.

Key words: TDOA, Genetic Algorithm(GA), Simulated Annealing(SA) algorithm, maximum likelihood function

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