The principle of the frequency estimation algorithm based on frequency offset correction was presented. The computation formula of the frequency estimation-s standard deviation of a complex sinusoidal signal in white Gauss noise was obtained. The value of parameter m was optimized when the data length was N, The algorithm can reach the minimum standard deviation when m was the integer closest to N/3. The Monte Carlo simulation results demonstrate that the algorithm based on frequency offset correction as the integer m is closest to N/3 has lower standard deviation than the interpolation method with Hanning window and the phase difference method, while retaining a flat profile in the frequency range away from the fast Fourier transforms(FFT) discrete spectral line. The m-optimized algorithm-s standard deviation is less and closer to the Cramer-Rao lower bound(CRLB) than the one as m is the integer closest to N/2 when signal noise ratio(SNR) is higher.
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