摘要
应用Kalman滤波方法,在按矩阵加权线性最小方差最优信息融合规则下,提出了带白色观测噪声的多通道ARMA信号的多传感器信息融合Wiener滤波器.它可统一处理信息融合滤波、平滑和预报问题.为了计算最优加权阵,提出了计算局部滤波误差互协方差阵的公式.同单传感器情形相比,可提高估计精度.一个带三传感器的目标跟踪系统的仿真例子说明了其有效性.
By using the Kalman filtering method and the linear minimum variance optimal fusion rule weighted by matrices, a multisensor information fusion Wiener filter is presented for the multichannel autoregressive moving average（ARMA） signals with white observation noise. It can handle the information fusion filtering, smoothing and prediction problems in a unified framework. In order to compute the optimal weighting matrices, the formula of computing the cross - covariance matrices among local filtering errors, is presented. Compared with the single sensor case, the estimation accuracy is improved. A simulation example for a target tracking system with three-sensor shows its effectiveness.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2005年第4期641-644,共4页
Control Theory & Applications
基金
国家自然科学基金资助项目(60374026)
黑龙江大学自动控制重点实验室资助项目(04-01).
