Adaptive frequency estimation with low sampling rates based on robust Chinese remainder theorem and IIR notch filter

In this paper, based on an adaptive IIR notch filter and a robust Chinese remainder theorem (CRT), we propose a frequency estimation algorithm from multiple undersampled signals. Our proposed algorithm can significantly reduce the sampling rates and provide more accurate estimates than the method based on adaptive IIR notch filter and sampling rates above the Nyquist rates does. We then present simulation results to verify the performance of our proposed algorithm for both stationary and nonstationary signals.