Overdetermined spectral analysis of short data records

The concept of using more than the minimal set of the normal equations was introduced in spectral analysis to counteract the hypersensitivity of the model's parameters. A simultaneous vertical and horizontal extension of the autocorrelation matrix leads to an overdetermined, order-extended system. The application of the overdetermined approach to the analysis of short signal frames is examined. A comparative study of the autocorrelation lags uses in the overdetermined matrices, based on the biased and unbiased autocorrelation estimators, as well as their estimation performance, is presented. The authors suggest use of the biased measure for low signal-to-noise ratio and short data records, since experimental results illustrate sensitivity of the unbiased measure to the noise ratio and frame length. However, when the conditions become better the unbiased measure tends to yield more accurate estimates.<
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