摘要
基于自噪声平滑器,本文提出了状态空间模型中噪声协方差的一种新的递推估计方法,给出了一种次优无偏极大后验(MAP)递推噪声协方差估值器,可应用于信号去卷和Kalman滤波,仿真例子说明了本文结果的有效性。
Based on white noise estimators, this paper presents a new recursive estimation approach to the noise covariances in the state-space model. Suboptimal unbiased maximum a posteriori (MAP) recursive estimators of noise covariances are given, which can be applied to signal deconvolution and Kalman filtering. Simulation example shows usefulness of proposed result.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
1990年第1期86-91,共6页
Control Theory & Applications
关键词
噪声协方差
递推估计
信号去卷
signal deconvolution
Kalman filtering
noise statistics estimators
white noise estimators
