Abstract
This paper compares performances of frequency estimations provided by different interpolation fast Fourier transform (FFT) algorithms under white Gaussian noises. Firstly, accuracies of frequency estimation algorithms are evaluated by deriving analytical expressions of variances of frequency estimation. Then, theoretical results are validated by means of computer simulations. It is shown that the trade-off between biases and variances of frequency estimation is unavoidable. From both theoretical and simulation results, it can be concluded that variances of frequency estimation are proportional to the noise variance and inverse proportional to the length of FFT.
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