title: Robust and Efficient Frequency Estimator for Undersampled Waveforms Based on Frequency Offset Recognition.
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.
authors.affiliation: School of Electronic Information Engineering, Tianjin University, Tianjin, China.
authors.forename: Xiangdong
authors.initials: X
authors.lastname: Huang
authors.affiliation: School of Electronic Information Engineering, Tianjin University, Tianjin, China.
authors.forename: Ruipeng
authors.initials: R
authors.lastname: Bai
authors.affiliation: School of Electronic Information Engineering, Tianjin University, Tianjin, China.
authors.forename: Xukang
authors.initials: X
authors.lastname: Jin
authors.affiliation: School of Electronic Information Engineering, Tianjin University, Tianjin, China.
authors.forename: Haipeng
authors.initials: H
authors.lastname: Fu
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio