摘要
对于带自回归滑动平均(ARMA)有色观测噪声的多传感器广义离散随机线性系统,应用奇异值分解,提出了广义系统多传感器信息融合状态滤波问题。基于Kalman滤波方法,在线性最小方差信息融合准则下,给出了按矩阵加权融合降阶稳态广义Kalman滤波器。为了计算最优加权,提出了局部滤波误差协方差阵的计算公式。一个Monte Carlo仿真例子说明了其有效性。
For muhisensor descriptor discrete-time stochastic linear systems with autoregressive moving average （ARMA） colored observation noises,using the singular value decomposition, the problem of multi-sensor information fusion state filter for descriptor systems is presented. Based on Kalman filtering method, a reduced order steadystate descriptor Kalman filter weighted by matrices is proposed under the linear minimum variance information fusion criterion. In order to compute the optimal weights, the formulas of computing the covariance matrices among local filtering errors are presented. A Monte Carlo simulation example shows its effectiveness.
出处
《科学技术与工程》
2009年第10期2544-2550,共7页
Science Technology and Engineering
基金
国家自然科学基金(60374026)
黑龙江科技学院引进人才启动基金(07-47)资助
