γ-LMS and its use in a noise-compensating adaptive spectral analysis technique

The application of an adaptive prediction error filter to autoregressive spectral analysis has been proposed by Lloyd Griffiths and is in use for the measurement of the frequencies of sinusoids It is well known that additive observation noise can bias these frequency estimates, thus limiting the useful applications of Griffiths technique to low noise environments. In the limit of white observation noise this paper develops a modified adaptive algorithm which incorporates a priori or measured noise power information so that the generated frequency estimates are unbiased. Unlike other bias removal techniques recently discussed, this technique can work with multiple sinusoids. The performance of this algorithm will be demonstrated through computer simulations and its convergence behavior will be discussed.