Journal of Systems Engineering and Electronics ›› 2010, Vol. 32 ›› Issue (7): 1522-1528.doi: 10.3969/j.issn.1001506X.2010.07.040

• 软件、算法与仿真 • 上一篇    下一篇

基于广义交互式遗传算法改进的粒子滤波技术

张〓焱1, 张志龙1, 陆〓琤2, 沈振康1   

  1. (1. 国防科学技术大学电子科学与工程学院ATR国家重点实验室, 湖南 长沙 410073;
    2. 陆军航空学院机载设备系, 北京 100869)
  • 出版日期:2010-07-20 发布日期:2010-01-03

Improved particle filtering technique based on broad interactive genetic algorithm

ZHANG Yan1, ZHANG Zhilong1, LU Cheng2, SHEN Zhenkang1   

  1. (1. ATR Key Laboratory, National Univ. of Defense Technology, Changsha 410073, China;
    2. Dept. of Airborne Avionice, Army Aviation Inst. Beijing 100869, China)
  • Online:2010-07-20 Published:2010-01-03

摘要:

基于一种广义交互式遗传算法对粒子滤波的重采样步骤进行改进,解决粒子滤波的退化和匮乏问题。该方法结合实际处理的优化问题,人为确定候选窗的范围和大小,利用改进型“拥挤因子模型”选择算子进行选择操作,在数学上确保了迭代过程中粒子的多样性,同时利用“完全算数交叉算子”实现交叉操作,这种交叉算子的优点是可行解空间关于交叉运算封闭,采用非一致变异算子实现变异操作,可有效地捕获可能出现的异常情况。仿真实验结果证明了这种改进后的滤波方法与扩展卡尔曼滤波(extended Kalman filtering, EKF)、标准粒子滤波和正则粒子滤波三种方法相比较,具有较好的迭代估计性能。

Abstract:

The resampling step of particle filtering based on a broad interactive genetic algorithm resolve particle degeneration and particle shortage. The range of selecting window is confirmed by human being and the improved selecting operator with jam gene is used to ensure the diversity of particle filtering in mathematics, and the absolute arithmetical crossing operator whose feasible solution space being close about crossing operation, and nonuniform mutation operator is used to capture all kinds of mutation. The result of simulating experiment shows that the algorithm has better iterative estimating capability than extended Kalman filtering (EKF), particle filtering (PF), and regulariztion particle filtering (RPF).