Dual Spectral Line Interpolation FFT Harmonic Analysis Using Kaiser Window

Dual spectral line interpolation FFT harmonic analysis using Kaiser window is a high-precision signal processing method primarily used for harmonic parameter detection in power systems or communication fields. This approach significantly improves frequency and amplitude measurement accuracy in traditional FFT analysis by combining the superior spectral leakage suppression characteristics of Kaiser window with dual spectral line interpolation algorithms.

During implementation, the first step involves applying a Kaiser window to the acquired time-domain signal. The Kaiser window features an adjustable β parameter that enables flexible control over the balance between main lobe width and side lobe attenuation according to practical requirements. After windowing, the signal is transformed to the frequency domain through FFT. Since actual signal frequencies often don't precisely align with integer multiples of the frequency resolution, simple FFT analysis would lead to significant fence effects.

The dual spectral line interpolation technique addresses this by selecting one spectral line on each side of the spectrum peak point and establishing equation systems using their amplitude ratio relationships. By solving these equations, the actual signal frequency, amplitude, and phase can be accurately estimated. Compared with single spectral line interpolation, the dual-line method provides better correction for errors caused by spectral leakage.

In MATLAB implementation, special attention should be paid to Kaiser window parameter selection, numerical stability handling of interpolation algorithms, and phase correction implementation details. Key functions include kaiser() for window generation, fft() for Fourier transformation, and polyfit() or similar functions for solving interpolation equations. This method can be effectively applied in power system harmonic analysis, radar signal processing, and other domains, providing more accurate input data for subsequent processing stages like channel estimation and parameter extraction.