Hanning Window FFT Interpolation Algorithm

To implement the Hanning window FFT interpolation algorithm, users must provide two key parameters: sampling frequency and FFT length. This algorithm enables precise calculation of harmonic characteristics including amplitude, frequency, and phase. The implementation typically involves applying a Hanning window function to the time-domain signal before performing FFT analysis, followed by interpolation around spectral peaks to achieve sub-bin frequency resolution. The sampling frequency parameter defines the number of samples acquired per second, while the FFT length determines the size of the sample window used for Fourier transformation. By employing Hanning window interpolation, the algorithm significantly reduces spectral leakage and provides more accurate harmonic parameter estimates, thereby enabling better characterization of signal properties. Common implementation steps include window function application, FFT computation, peak detection, and polynomial interpolation around detected peaks.