改进的粒子滤波算法在目标跟踪中的应用

粒子滤波算法中通常采用先验转移概率代替重要性函数,由此重要性密度函数对后验函数的偏差将增大。将小波去噪应用到粒子滤波过程中,降低了偏差,提高了粒子算法的滤波精度,并将该算法应用到目标跟踪的过程中,通过仿真证实该方法能够提高粒子滤波精度。

The Application of Improved Particle Filter in Target Tracking

Particle filter uses the prior probability instead of importance density function,so the deviation between importance density function and posterior probability function.This paper applies wavelet denoising into the process of particle filter to reduce its deviation and improve the filter precision of particle algorithm,and applies this algorithm into the process of target tracking,improving the particle filter precision demonstrated through simulation.