Abstract
A novel algorithm is proposed for frequency estimation of a single complex exponential signal or a real sinusoid signal in additive white Gaussian noise (AWGN). The proposed algorithm consists of a coarse search and a fine search, where the coarse search can be accomplished by maximum likelihood (ML) estimation, while the fine search performs a frequency interpolation via time-domain zero padding before applying discrete Fourier transform (DFT) with a novel residue frequency estimator proposed. Simulation results demonstrate that improved performance can be achieved by our proposed estimator based on zero-padding data sequence.
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