系统工程与电子技术 ›› 2019, Vol. 41 ›› Issue (2): 254-258.doi: 10.3969/j.issn.1001-506X.2019.02.05

• 电子技术 • 上一篇    下一篇

改进的自适应遗传算法在TDOA定位中的应用

王生亮1,2, 刘根友1, 高铭1,2, 王嘉琛1,2, 王彬彬1,2   

  1. 1.中国科学院测量与地球物理研究所大地测量与地球动力学国家重点实验室, 湖北 武汉 430077;
    2.中国科学院大学地球与行星科学学院, 北京 100049
  • 出版日期:2019-01-25 发布日期:2019-01-24

Application of improved adaptive genetic algorithm in TDOA location

WANG Shengliang1,2, LIU Genyou1, GAO Ming1,2, WANG Jiachen1,2, WANG Binbin1,2   

  1. 1. State Key Laboratory of Geodesy and Earth’s Dynamics, Institute of Geodesy and Geophysics,
    Chinese Academy of Sciences, Wuhan 430077, China; 2. College of Earth and Planetary Sciences,
    University of Chinese Academy of Sciences, Beijing 100049, China
  • Online:2019-01-25 Published:2019-01-24

摘要: 针对无线通信到达时间差(time difference of arrival,TDOA)定位技术位置解算为复杂的非线性方程最优化问题,采用实数编码遗传算法,提出了改进的自适应遗传算法。该算法设计了自适应交叉率和变异率的计算公式,考虑了随着进化代数增加种群的整体变化,同时考虑了每代种群不同个体适应度的作用,并引入最优保存策略防止优良个体的破坏,能有效产生新的个体进而摆脱局部最优值的搜索达到全局最优解。仿真结果表明,改进的遗传算法性能稳定,进化收敛速度和TDOA定位估计精度都有较大的提高。

Abstract: The solution of time difference of arrival (TDOA) location technology for wireless communication is a complex nonlinear equation optimization problem. This paper adopts a realencoded genetic algorithm, and proposes an improved adaptive genetic algorithm which designs the adaptive crossover rate and mutation rate formula, considers not only the influence of evolutionary generations 〖JP2〗on the population, but also the fitness of different individuals〖JP〗 in each generation. The elitist strategy is introduced to prevent the destruction of good individuals, effectively generate new individuals and then get rid of the local optimal value search to achieve the global optimal solution. The simulation results show that the performance of the algorithm is stable, and the speed of evolutionary convergence and the accuracy of TDOA location estimation are greatly improved.