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An Improved Algorithm for High-Precision Frequency Estimation

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Advances in Intelligent Automation and Soft Computing (IASC 2021)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 80))

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Abstract

Wide ranges of signal-to-noise ratios would cause frequency estimation algorithm to perform unstable anti-noise characteristics, low estimation accuracy, and poor realizability in engineering experiments. To resolve such impacts, this paper proposes an improved algorithm for a two-step frequency estimation of a complex sinusoidal signal submerged in Gaussian white noise - the fixed Quinn algorithm integrates with the Aboutanios and Mulgrew algorithm to compose a hybrid high-precision and robust frequency estimation algorithm. Through simulations, the results proved that the estimator is asymptotically unbiased with its root mean square error (RMSE) and is further closed to the Cramer–Rao lower bound (CRLB). In addition, the improved algorithm possesses anti-noise characteristics, stronger algorithm robustness, and can be easily applied in various signal processing contexts.

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Authors and Affiliations

  1. Key Laboratory of Radar Imaging and Microwave Photonics, College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Shihong Chen, Minghai Pan & Xudong Wang

Authors
  1. Shihong Chen
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  2. Minghai Pan
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  3. Xudong Wang
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Corresponding author

Correspondence to Shihong Chen .

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Editors and Affiliations

  1. Electronics and Computer Engineering Technology, Indiana State University, Terre Haute, IN, USA

    Xiaolong Li

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Chen, S., Pan, M., Wang, X. (2022). An Improved Algorithm for High-Precision Frequency Estimation. In: Li, X. (eds) Advances in Intelligent Automation and Soft Computing. IASC 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-81007-8_22

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