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A Novel Low-Complexity Frequency Estimation Algorithm for Industrial Internet-of-Things Applications.
- Source :
-
IEEE Transactions on Instrumentation & Measurement . 2021, Vol. 70, p1-10. 10p. - Publication Year :
- 2021
-
Abstract
- In this article, we present a novel autocorrelation-based frequency estimation algorithm for single-tone sinusoidal signals. In comparison to other state-of-the-art frequency estimation methods, the proposed one provides a better tradeoff between accuracy, complexity, and estimation range. In particular, the algorithm is able to achieve the Cramer–Rao lower bound for moderate and high signal-to-noise ratio, and its implementation is feasible even in resource-constrained microcontrollers, as those commonly used in the Industrial Internet-of-Things (IIoT) applications and low-cost instrumentation. Finally, we investigate the performance of the algorithm in the case of a practical IIoT application, i.e., frequency estimation of unbalanced three-phase power systems, showing that it outperforms several other autocorrelation-based estimators. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189456
- Volume :
- 70
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Instrumentation & Measurement
- Publication Type :
- Academic Journal
- Accession number :
- 170414914
- Full Text :
- https://doi.org/10.1109/TIM.2020.3034629