Multisensor Information Fusion Wiener Filter for ARMA Signals

摘要：

By the modern time series analysis method and white noise estimators, 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 filtering error variances and cross-covariances are given, which are applied to compute optimal weighting coefficients. Compared with the single sensor case, the accuracy of the fused filter is improved. A simulated example shows its effectiveness.

关键词： multisensor information fusion optimal fusion rule weighted by scalars Wiener filter augmented state space model modern time series analysis method

作者: Li-Xin Yang Zi-Li Deng Li-Jun Zhang

作者单位: Department of Automation, Harbin Engineering University, Harbin, China Department of Automation, Heilongjiang University, Harbin, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 2431-2434

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）