Parameter estimation using the autocorrelation of the discrete Fourier transform

Abstract

Optimal parameter estimation algorithms are developed using the maximum likelihood technique, when no statistics are available for the parameter. Sub-optimal parameter estimates, using one sample of the autocorrelation of the DFT, have been developed previously. In this paper, maximum likelihood estimates are derived, given the auto-correlation function of the received signal's DFT. These estimates sometimes require less computation time than conventional estimates, and frequently have a closed form or simple iterative implementation.