Interpolation techniques for real-time multifrequency waveform analysis

It is well-known that in discrete-Fourier-transform- (DFT-) based waveform analysis of multifrequency signals, spectral parameter accuracy can be increased by windowing the time samples and interpolating the DFT coefficients. It is shown that some relationships used in interpolation are affected very little by the number of processed samples, so that only the characteristics of the analyzed signal and the required accuracy affect the choice of this parameter. In particular, this makes the approach well suited for real-time analysis of signals with slowly time-varying spectra. Polynomial approximations of some relationships reduce the processing effort and, allow a greater freedom in the choice of the window functions, improving both accuracy and frequency resolution