Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping

Joint Authors

Zhou, Shen
Rongfang, Liu

Source

Mathematical Problems in Engineering

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-6, 6 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-04-14

Country of Publication

Egypt

No. of Pages

6

Main Subjects

Civil Engineering

Abstract EN

In the case of low signal-to-noise ratio, for the frequency estimation of single-frequency sinusoidal signals with additive white Gaussian noise, the phase unwrapping estimator usually performs poorly.

In this paper, an efficient and accurate method is proposed to address this problem.

Different from other methods, based on fast Fourier transform, the sampled signals are estimated with the variances approaching the Cramer-Rao bound, followed with the maximum likelihood estimation of the frequency.

Experimental results reveal that our estimator has a better performance than other phase unwrapping estimators.

Compared with the state-of-the-art method, our estimator has the same accuracy and lower computational complexity.

Besides, our estimator does not have the estimation bias.

American Psychological Association (APA)

Zhou, Shen& Rongfang, Liu. 2019. Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1196981

Modern Language Association (MLA)

Zhou, Shen& Rongfang, Liu. Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping. Mathematical Problems in Engineering No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1196981

American Medical Association (AMA)

Zhou, Shen& Rongfang, Liu. Efficient and Accurate Frequency Estimator under Low SNR by Phase Unwrapping. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1196981

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1196981