Frequency estimation using warped discrete Fourier transform

Abstract

As a complement to the periodogram, low-cost frequency estimators are of interest. In this paper we introduce a new approach for single frequency estimation using the warped discrete Fourier transform (WDFT). The WDFT corresponds to sampling the z-transform of a finite length sequence at warped points in the frequency domain by using an allpass function which allows to increase the frequency resolution locally. We focus on a first-order allpass function with a complex valued warping parameter. If the warping parameter is zero, the WDFT reduces to the discrete Fourier transform. Performance and complexity aspects of the proposed algorithm are discussed and finally, we provide an perspective on how the WDFT can be used to reduce the complexity of existing estimators in the case of multiple sinusoids.