多传感器信息融合Wiener反卷积平滑器

Multi-sensor Information Fusion Wiener Deconvolution Smoother

应用现代时间序列分析方法,基于ARMA新息模型和增广的状态空间模型,提出了按标量加权多传感器最优信息融合ARMA信号Wiener反卷积平滑器,给出了计算局部平滑器误差方差和互协方差的计算公式,它们可被用于计算最优加权系数.同单传感器情形相比,可提高融合平滑器的精度。一个仿真例子说明其有效性。

By the modern time series analysis methods, based on ARMA innovation model and augmented state space model, muhisensor optimal information fusion ARMA signal Wiener deconvolusion smoother weighted by scalars is proposed. The formulas of computing the local smoother error variances and cross-covariances are given, which are applied to compute optimal weights. Compared to the single sensor case, the accuracy of the fused smoother is improved. A simulation example shows its effectiveness.