Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (28): 195-197.

• 图形、图像、模式识别 • Previous Articles     Next Articles

Particle filter target tracking algorithm combining artificial immune

CAO Weijie,TONG Mu,TANG Minghao   

  1. College of Information Science and Technology,Donghua University,Shanghai 201620,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2011-10-01 Published:2011-10-01

一种结合人工免疫的粒子滤波目标跟踪算法

曹伟杰,童 牧,唐明浩   

  1. 东华大学 信息科学与技术学院,上海 201620

Abstract: For the traditional particle filter tracking algorithm with the problem of particle degeneration,a particle filter tracking algorithm combining artificial immune is presented.The method utilizes the principle of immunology,makes the feature of target template as antigen and the feature of every particle’s corresponding area as antibody,transforms the problem of matching into the affinity between antigen and antibody,keeps the antibody with high affinity by the way of clone and gets rid of the antibody by means of variation,thus the result converges at the global optimal solution rapidly.The diversity of antibody solves the degeneration of traditional particle filter effectively.Using the method in target tracking,the simulation’s results show that the effective sample of particle set is improved apparently.

Key words: particle filter, artificial immune algorithm, particle degeneration, target tracking, effective sample

摘要: 针对传统的粒子滤波跟踪算法存在粒子退化的问题,提出了一种结合人工免疫的粒子滤波跟踪算法。该方法利用免疫学原理,将目标模板特征作为抗原,每个粒子对应区域的特征作为抗体,匹配问题转化为抗原和抗体的亲和力问题,通过克隆的方式保留亲和力大的抗体,采用变异的手段去除亲和力小的抗体,从而使结果快速收敛于全局最优解。抗体的多样性有效解决了传统粒子滤波的退化问题。将该方法应用到目标跟踪技术中,仿真结果表明,粒子集的有效样本得到了明显的提高。

关键词: 粒子滤波, 人工免疫, 粒子退化, 目标跟踪, 有效样本