Frequency determination from truly sub-Nyquist samplers based on robust Chinese remainder theorem

In this paper, a truly sub-Nyquist sampling method for frequency estimation of sinusoidal signals in noise is presented. Basically speaking, sinusoidal signals are first sampled at multiple sampling rates lower than the Nyquist rate, and then a robust Chinese remainder theorem (CRT) is proposed to estimate the frequencies of interest from the aliased frequencies obtained by taking the discrete Fourier transform of the collected samples in each undersampled waveform. Compared with compressed sensing, this method can be easily implemented from the hardware point of view. This paper provides a thorough overview of the existing research results on the robust CRT during the last decade, and discusses some related open problems as well.