Refined Algorithm for Frequency Estimation of A Real Sinusoid in Smart Grid

In this thesis report, a novel efficient algorithm for the smart grid is proposed to estimate the frequency of a real sinusoidal signal with additive white Gaussian noise. This method modifies the dichotomous search estimator for complex exponential signal model to fit the real sinusoidal signal model, which considers and calculates the spectral leakage based on the original interpolation on Fourier coefficients. Simulation result are also shown to prove the proposed algorithm could generate more accurate frequency estimation in various signal-to-noise(SNR) situations, tested frequency and phase shift of the signal. The root-mean-squared-error(RMSE) of the simulated results performs similar results as the Cramer-Rao Lower Bound(CRLB) with sufficient iterative processes.

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