Deng Zi-li, Gao Yuan, Li Yun, Wang Xin . Multisensor Information Fusion Steady-State Optimal Wiener Deconvolution Filter[J]. Journal of Electronics & Information Technology, 2005, 27(4): 670-672.
Citation:
Deng Zi-li, Gao Yuan, Li Yun, Wang Xin . Multisensor Information Fusion Steady-State Optimal Wiener Deconvolution Filter[J]. Journal of Electronics & Information Technology, 2005, 27(4): 670-672.
Deng Zi-li, Gao Yuan, Li Yun, Wang Xin . Multisensor Information Fusion Steady-State Optimal Wiener Deconvolution Filter[J]. Journal of Electronics & Information Technology, 2005, 27(4): 670-672.
Citation:
Deng Zi-li, Gao Yuan, Li Yun, Wang Xin . Multisensor Information Fusion Steady-State Optimal Wiener Deconvolution Filter[J]. Journal of Electronics & Information Technology, 2005, 27(4): 670-672.
By the modern time series analysis method, based on the AutoRegressive Moving Average(ARMA) innovation model and Lyapunov equation, a mulisensor information fusion Wiener deconvolution filter is presented for single channel ARMA signals. It avoids the Riccati equation and can be applied to design the self-tuning information fusion filter for systems with unknown model parameters and unknown variances. A simulation example shows its effectiveness.
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