摘要
文中介绍基于白噪声滤波器和平滑器的改进的Sage和Husa噪声统计估值器及相应的自适应Kalman滤波器,可处理未知常的和时变的噪声统计估计问题。仿真结果验证了改进滤波器在精度和收敛速度上的优越性。
This article presents an improved Sage and Husa noise statistical estimator and relevant adaptable Kalman filter based on white noise filter. This algorithm can handle problems of unknown parameters and constantly changed noise statistical estimation, and enhance the precision. The result of simulation proves the superiority of improved filter on precision and convergence speed.
出处
《国外电子测量技术》
2006年第6期69-71,共3页
Foreign Electronic Measurement Technology
