带MA有色观测噪声的单通道多传感器信息融合Wiener滤波器

Multisensor Information Fusion Wiener Filter for Single-channel ARMA Signals with MA Coloured Observation Noise

应用现代时间序列分析方法,基于ARMA新息模型、白噪声估值器和观测预报器,对带滑动平均(MA)有色观测噪声的单通道ARMA信号,在线性最小方差最优信息融合准则下,提出了多传感器信息融合Wiener滤波器,可统一处理滤波、平滑和预报问题。提出了用于得到最优加权系数的局部滤波误差方差和协方差计算公式。同单传感器情形相比,可提高滤波精度。一个目标跟踪系统的仿真例子说明了其有效性。

Using the modern time series analysis method,based on the autoregressive moving average (ARMA) innovation model, white noise estimator and measurement predictor,under the linear minimum variance optimal fusion criterion,a multisensor information fusion Wiener filter is respectively presented for the single-channel ARMA signals with moving average (MA) coloured observation noise.It can handle the filtering, smoothing and prediction problem in a unified framework.The formula of computing variance and covariance among local filtering errors is presented, which is applied to obtain the optimal weighting coefficients. Compared with the single sensor case, the accuracy of the filter is improved.A simulation example for the target tracking system shows their effectiveness.