Information Fusion Indentification of Mutisensor ARMA Model with Colored Measurement Noise
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For the unknown autoregressive moving average(ARMA) model with known colored measurement noise,a two-stage information fusion identification method is presented: In the first stage,the local and fused estimates of the autoregressive(AR) paraments are obtained by the recursive instrumental variable(RIV),and in the second stage,the local and fused estimates of the moving average(MA) paraments and noise variance are obtained by the Gevers-Wouters algorithm and by solving linear equation by the pseudoinverse.These fused estimators have consistency.This method can be applied to signal processing with respect to speech enhancement.A simulation example shows its effectiveness.