A new algorithm for the estimation of the frequency of a complex exponential in additive Gaussian noise

Abstract

This letter presents a new algorithm for the precise estimation of the frequency of a complex exponential signal in additive, complex, white Gaussian noise. The discrete Fourier transform (DFT)-based algorithm performs a frequency interpolation on the results of an N point complex fast Fourier transform. For large N and large signal to noise ratio, the frequency estimation error variance obtained is 0.063 dB above the Cramer–Rao Bound. The algorithm has low computational complexity and is well suited for real time applications.