摘要
应用Kalman滤波方法,基于白噪声估计理论,在线性最小方差最优信息融合准则下,提出了多通道ARMA 信号的两传感器信息融合稳态最优Wiener滤波器、平滑器和预报器;给出了最优加权阵和最小融合误差方差阵。与单传感器情形相比,可提高滤波精度。一个雷达跟踪系统的仿真例子说明了其有效性。
Using the Kalman filtering method, based on white noise estimation theory, under the linear minimum variance information fusion criterion, two-sensor information fusion steady-state optimal Wiener filter, smoother and predictor are presented for the multichannel Auto-Regressive Moving Average（ARMA） signals, where the optimal weighting matrices and minimum fused error variance matrix are given. Compared with the single sensor case, the accuracy of the filter is improved. A simulation example of a radar tracking system shows its effectiveness.
出处
《电子与信息学报》
EI
CSCD
北大核心
2005年第9期1416-1419,共4页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60374026)资助课题
