Weighted minimum noise subspace method for blind system identification

Abstract Blind identification of single-input multiple-outputs FIR system has attracted much attention during the past few years. This interest is due to the fact that accurate system parameter estimates can be obtained using only the second-order statistics of the system outputs. In this paper, a weighted minimum noise subspace W-MNS estimate of the FIR system parameters is developed. The asymptotic variances of the W-MNS system parameter estimates are derived, and a statistically optimal weighting matrix is proposed. The optimal W-MNS estimates of the unknown system parameters are shown to be significantly more accurate than the existing MNS estimates.

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