摘要: |
通过将交互多模型(IMM)算法和粒子滤波(SIS)算法结合,提出了一种新的IMM~SIS算法。在每个模型中,都有一个标准的粒子滤波器,模型之间的交互与传统的IMM一样。由于在新的算法中,每个模型中粒子滤波都保证固定数量的粒子,因此不会出现粒子退化和贫乏现象。仿真证明了新的IMM—SIS算法在收敛速度和精度方面都要优于传统的IMM—EKF算法。 |
关键词: 机动目标跟踪 交互多模式模型 序贯重要采样 收敛速度 |
DOI:10.3969/j.issn.1001-893X. |
修订日期:2007-05-11 |
基金项目: |
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A Novel Sequential Importance Sampling Algorithm Based on Interacting Multiple Model |
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Abstract: |
A novel method for multiple model particle filtering for Markovian switching systems is introduced.This new method is a combination of the interacting multiple model(IMM)filter and particle filter.A regularized particle filter is running in every mode.The mixing and interaction is similar to that in a conventional IMM filter.Furthermore,the new method keeps a fixed number of particles in each mode,and therefore it avoids the particle degeneracy and impoverishment phenomenon.Simulations show that the tracking speed and accuracy of the IMM-SIS algorithm are better than those of the IMM-EKF. |
Key words: motive target tracking,interacting multiple model(IMM),sequential importance sampling(SIS),convergence speed |