摘要
粒子滤波适用于非线性模型和非高斯噪声的目标跟踪,但其大计算量,限制了实时应用。硬件实现是解决此问题的有效途径。本文针对粒子滤波的第三个步骤-再采样的硬件实现,引入动态基准位置和动态阈值设置,将“粒子-标签”残差再采样的高效定点实现方法进行扩展,使其可以直接对非归一化的权值进行再采样。免去需要进行大量除法运算的权值归一化操作,提高粒子滤波的实时性。实验结果表明其有效性。
particle filter has been proved to be a powerful tool for object tracking in nonlinearity and non-Gaussianity setting,but large computational cost limits its real-time application. Hardware implementation should be an efficient approach to overcome this drawback. For hardware implementation of resampling-the third stage of particle filter, dynamic benchmark position and dynamic threshold are introduced, extending "particle-tagging" method to process non-normalization weights directly, avoiding a large number of division calculations for normalization, and increasing real-time performance of particle filter. Experiment results demonstrate its validity.
出处
《信号处理》
CSCD
北大核心
2007年第1期97-100,共4页
Journal of Signal Processing
基金
航天"十五"预研基金项目资助(编号:413160203)
关键词
粒子滤波
硬件实现
再采样
动态基准位置
非归一化权值
particle filter
hardware implementation
resampling
dynamic benchmark position
non-normalization weights