Robust and Efficient Frequency Estimator for Undersampled Waveforms Based on Frequency Offset Recognition

Xiangdong Huang, Ruipeng Bai, Xukang Jin and Haipeng Fu

PLOS ONE, 2016, vol. 11, issue 10, 1-12

Abstract: This paper proposes an efficient frequency estimator based on Chinese Remainder Theorem for undersampled waveforms. Due to the emphasis on frequency offset recognition (i.e., frequency shift and compensation) of small-point DFT remainders, compared to estimators using large-point DFT remainders, it can achieve higher noise robustness in low signal-to-noise ratio (SNR) cases and higher accuracy in high SNR cases. Numerical results show that, by incorporating a remainder screening method and the Tsui spectrum corrector, the proposed estimator not only lowers the SNR threshold of detection, but also provides a higher accuracy than the large-point DFT estimator when the DFT size decreases to 1/90 of the latter case.

Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0163871

DOI: 10.1371/journal.pone.0163871

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