一种抗野值的Kalman滤波器

Kalman Filter Restraining Outliers

在目标跟踪系统中,由于杂波的存在,往往使跟踪检测数据中含有大量、成片的野值,造成系统跟踪精度下降。本文通过对检测数据中新息特性的分析,给出了检测数据中野值的判定方法,通过重新构造状态估计来消除野值的影响。仿真结果证明了该方法可有效的剔除野值,提高跟踪系统的跟踪精度。

In target tracking system, the outliers will be included in measurements data because of the clutter environment, which decreases the tracking accuracy. In this paper, we propose a method to detect the outliers and reconstruct the state estimate to reduce the influence of outliers. Using the criteria, we can determine the measurements weather is outliers or not. The simulation results prove that the method can restrain the outliers and increase the accuracy of the target tracking system.