English
Optimal and self-tuning information fusion Kalman multi-step predictor
文件大小：
1271k
资源说明：Based on the optimal fusion algorithm weighted by matrices
in the linear minimum variance (LMV) sense, a distributed
optimal information fusion for the steady-state Kalman multi-step
predictor is given for discrete linear stochastic control systems
with multiple sensors and correlated noises, where the same
sample period is assumed. When the noise statistics information
is unknown, the distributed information fusion estimators for the
noise statistics parameter
in the linear minimum variance (LMV) sense, a distributed
optimal information fusion for the steady-state Kalman multi-step
predictor is given for discrete linear stochastic control systems
with multiple sensors and correlated noises, where the same
sample period is assumed. When the noise statistics information
is unknown, the distributed information fusion estimators for the
noise statistics parameter
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