多传感器信息融合ARMA信号Wiener滤波器

应用现代时间序列分析方法,基于自回归滑动平均(autoregressive moving average,ARMA)新息模型和增广的状态空间模型,在线性最小方差按标量加权最优融合规则下,对带白色和有色观测噪声的单通道ARMA信号,提出了多传感器最优分布式融合Wiener滤波器。给出了计算局部滤波器误差方差和互协方差的公式,它们可被用于计算最优加权系数。同单传感器情形相比,可提高融合滤波器的精度。一个带三传感器的跟踪系统的仿真例子说明其有效性。

Multisensor information fusion ARMA signal Wiener filter

By the modern time series analysis method,based on the autoregressive moving average(ARMA) innovation model and augmented state space model,under the linear minimum variance optimal fusion rule weighted by scalars,a multisensor optimal distributed fusion Wiener filter is proposed for single channel ARMA signals with white and colored measurement noises.The formulas of computing local filter error variances and cross-covariance are given,which are applied to compute optimal weighting coefficients.Compared with the single sensor case,the accuracy of the fused filter is improved.Simulation example of a tracking system with three sensors shows its effectiveness.