Reconstruction of undersampled periodic signals

Under certain conditions, a periodic signal of unknown fundamental frequency can still be recovered when sampled below the Nyquist rate, or twice the highest frequency present in the waveform. A new sampling criterion has been proposed which enumerates such conditions. It has been shown that in theory, if the signal and sampling frequencies are not integrally related, and the signal is band-limited (to a range the extent of which is known but otherwise unrestricted), then the signal waveshape can always be recovered. If the fundamental frequency is known to lie within a range not spanning any multiple of half the sampling rate, then the temporal scaling for the reconstructed waveform can be determined uniquely, as well. Procedures have also been proposed for reducing time-scale ambiguity when the latter condition is not met. A previously presented time domain algorithm for reconstructing aliased periodic signals has been implemented and modified. A new algorithm, operating in the frequency domain, has been proposed and implemented. In the new algorithm, the signal fundamental frequency is first estimated from the discrete Fourier transform of the aliased data through an iterative procedure. This estimate is then used to sort the aliased harmonics.