多传感器单通道信息融合Wiener滤波器

应用现代时间序列分析方法，对于带白色观测噪声的单通道ARMA信号，基于ARMA新息模型，提出了多传感器线性最小方差最优信息融合Wiener滤波器，可统一处理滤波、平滑和预报问题。同单传感器情形相比，可提高滤波精度、算法简单、便于实时应用。一个跟踪系统的仿真例子说明了其有效性。

Multisensor Single Channel Information Fusion Wiener Filter

By the modern time series analysis method, based on the autoregressive moving average(ARMA) innovation model, the multisensor single channel optimal information fusion Wiener filter is presented under the linear minimum variance fusion criterion for single channel ARMA signals with white observation noise. It can handle the filtering, smoothing and prediction problems in a unified framework. Compared with the single sensor case, the accuracy of the filter is improved. Its algorithm is simple and suitable for the real time applications. A simulation for a tracking system shows its effectiveness.