Frequency Estimation of Single-Tone Sinusoids Under Additive and Phase Noise

Almoosawy, Asmaa Nazar; Hussain, Zahir M.; Murad, Fadel A.

doi:10.14569/ijacsa.2014.050916

Cited by 2 publications

(2 citation statements)

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“…1). ( 25) is more accurate than (26) in this range. For CiR > 2 the results of ( 25) and ( 26) are close to each other.…”

Section: Comparison Of Errors' Expressionsmentioning

confidence: 82%

“…The more signals were distorted by noise the more the DFT-based method was preferred and vice versa. The main conclusions from it can be found in [26] and [27], where a method based on the FFT and the Prony's method were compared and the second was more accurate in the case of harmonic components being present in an analysed signal. In this paper eight (Prony LS, TLS, ESPRIT and five 3-point IpDFT methods) estimation methods are compared in respect of both their estimation accuracy and estimation speed.…”

Section: Introductionmentioning

confidence: 99%

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Metrology and Measurement Systems

Borkowski

Kania

Mroczka

2018

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The paper deals with frequency estimation methods of sine-wave signals for a few signal cycles and consists of two parts. The first part contains a short overview where analytical error formulae for a signal distorted by noise and harmonics are presented. These formulae are compared with other accurate equations presented previously by the authors which are even more accurate below one cycle in the measurement window. The second part contains a comparison of eight estimation methods (ESPRIT, TLS, Prony LS, a newly developed IpDFT method and four other 3-point IpDFT methods) in respect of calculation time and accuracy for an ideal sine-wave signal, signal distorted by AWGN noise and a signal distorted by harmonics. The number of signal cycles is limited from 0.1 to 3 or 5. The results enable to select the most accurate/ fastest estimation method in various measurement conditions. Parametric methods are more accurate but also much slower than IpDFT methods (up to 3000 times for the number of samples equal to 5000). The presented method is more accurate than other IpDFT methods and much faster than parametric methods, which makes it possible to use it as an alternative, especially in real-time applications.

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“…1). ( 25) is more accurate than (26) in this range. For CiR > 2 the results of ( 25) and ( 26) are close to each other.…”

Section: Comparison Of Errors' Expressionsmentioning

confidence: 82%

Section: Introductionmentioning

confidence: 99%