The conventional fast Fourier transforms(FFT) approach is susceptible to noise and has a low-frequency resolution with short sampling windows. This is a bottleneck problem for accurately monitoring harmonic and interharmonic. A new method is proposed to detect the parameters of harmonic and interharmonic in this study. At the beginning, the cross-correlation function and FFT estimate the rough values of frequency and phase. Next, the error between the rough and true values is derived. Then, the incoherence of signal and noise is used to create the cost function, and the optimal initial value is computed from the rough values and the error. Finally, the initial value is used in cost function iteration, the so-called Newton–Raphson method, to calculate the frequency and phase of harmonic and interharmonic. The least squares method is used to compute the amplitudes of harmonic and interharmonic. The proposed method allows adaptively selecting the basis function for the cost function instead of using the traditional orthogonal basis. Therefore, it achieves the super-resolution evaluation of harmonic and interharmonic frequency. The simulation results demonstrate that the proposed method provides high accuracy of parameter estimation and strong noise immunity.