摘要
对于带相关噪声系统 ,基于稳态Kalman滤波器和自回归滑动平均 (ARMA)新息模型 ,提出了统一的渐近稳定的Wiener状态滤波器 ,可统一处理状态滤波 ,平滑和预报问题 .它们构成了一种新的时域Wiener滤波算法 .揭示了Kalman滤波器与Wiener滤波器之间的关系 .
Based on the steady-state Kalman filter and autoregressive moving average (ARMA) innovation model,the unified asymptotically stable Wiener state filters are presented for systems with correlated noises,which can handle the state filtering,smoothing and prediction problem in a unified framework.They constitute a new time-domain Wiener filtering algorithm.The relation between the Kalman filters and Wiener filters is discovered.A simulation example for a target tracking system has shown their effectiveness.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2004年第6期1003-1006,共4页
Control Theory & Applications
基金
国家自然科学基金项目 (60 3 740 2 6)
