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Signal enhancement of radio frequency power measurement in 1/f noise

One of the prevalence challenges in the radio frequency (RF) power sensor development is to reduce noise in the acquired signal. The noise in the signal subsequently contributes to the error in the measurement of signal parameters. Sources of noise could come from the chain of signal conditioning an...

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Main Author: Zali, Aida Amira
Format: Thesis
Language:English
Published: 2018
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/101842/1/AidaAmiraZaliMSKE2018.pdf
http://eprints.utm.my/id/eprint/101842/
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spelling my.utm.1018422023-07-17T02:33:50Z http://eprints.utm.my/id/eprint/101842/ Signal enhancement of radio frequency power measurement in 1/f noise Zali, Aida Amira TK Electrical engineering. Electronics Nuclear engineering One of the prevalence challenges in the radio frequency (RF) power sensor development is to reduce noise in the acquired signal. The noise in the signal subsequently contributes to the error in the measurement of signal parameters. Sources of noise could come from the chain of signal conditioning and acquisition in the sensor circuitry. The assumption of additive white Gaussian noise (AWGN) to model a measurement is not valid since many applications such as in RF power measurement has the noise coloured with 1/f spectrum characteristics. With this characteristics, the assumption of independent and identically distributed (IID) used in signal detection and estimation becomes not valid. By whitening process, the 1/f noise characteristics can be converted to be similar to white noise. The analysis results of decimation, linear prediction, Burg algorithm and chopper with averaging shows that the proposed methods can be used effectively. Both Burg algorithm and linear prediction are more complex due to the need to perform matrix inversion. The decimation and chopper with averaging are the least complex but it could only meet the requirements if the sample size is more than 300 samples. After performing the whitening, the wavelet transform and de-noising are implemented to remove noise as much as possible while preserving the signal characteristics. As results, it can be seen that the noise is removed while the characteristics of the pulse signal is preserved by the Haar wavelet. However, the recovered signal is distorted when using Daubechies 5 wavelet with significant reduction in noise. Based on the result for RF power measurement for different whitening methods in Monte Carlo simulation, Burg algorithm yields the highest total variance reduction which is 97.13%, followed by the linear prediction which is 90.3%, decimation 64.11% and lastly, chopper with averaging, 3.10% for SNR of 8 dB. Although Burg algorithm is more complex compared to decimation, it preserves all the signal samples which is more suitable for pulse signals and it is the best whitening method used in this research. 2018 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/101842/1/AidaAmiraZaliMSKE2018.pdf Zali, Aida Amira (2018) Signal enhancement of radio frequency power measurement in 1/f noise. Masters thesis, Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:145043
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zali, Aida Amira
Signal enhancement of radio frequency power measurement in 1/f noise
description One of the prevalence challenges in the radio frequency (RF) power sensor development is to reduce noise in the acquired signal. The noise in the signal subsequently contributes to the error in the measurement of signal parameters. Sources of noise could come from the chain of signal conditioning and acquisition in the sensor circuitry. The assumption of additive white Gaussian noise (AWGN) to model a measurement is not valid since many applications such as in RF power measurement has the noise coloured with 1/f spectrum characteristics. With this characteristics, the assumption of independent and identically distributed (IID) used in signal detection and estimation becomes not valid. By whitening process, the 1/f noise characteristics can be converted to be similar to white noise. The analysis results of decimation, linear prediction, Burg algorithm and chopper with averaging shows that the proposed methods can be used effectively. Both Burg algorithm and linear prediction are more complex due to the need to perform matrix inversion. The decimation and chopper with averaging are the least complex but it could only meet the requirements if the sample size is more than 300 samples. After performing the whitening, the wavelet transform and de-noising are implemented to remove noise as much as possible while preserving the signal characteristics. As results, it can be seen that the noise is removed while the characteristics of the pulse signal is preserved by the Haar wavelet. However, the recovered signal is distorted when using Daubechies 5 wavelet with significant reduction in noise. Based on the result for RF power measurement for different whitening methods in Monte Carlo simulation, Burg algorithm yields the highest total variance reduction which is 97.13%, followed by the linear prediction which is 90.3%, decimation 64.11% and lastly, chopper with averaging, 3.10% for SNR of 8 dB. Although Burg algorithm is more complex compared to decimation, it preserves all the signal samples which is more suitable for pulse signals and it is the best whitening method used in this research.
format Thesis
author Zali, Aida Amira
author_facet Zali, Aida Amira
author_sort Zali, Aida Amira
title Signal enhancement of radio frequency power measurement in 1/f noise
title_short Signal enhancement of radio frequency power measurement in 1/f noise
title_full Signal enhancement of radio frequency power measurement in 1/f noise
title_fullStr Signal enhancement of radio frequency power measurement in 1/f noise
title_full_unstemmed Signal enhancement of radio frequency power measurement in 1/f noise
title_sort signal enhancement of radio frequency power measurement in 1/f noise
publishDate 2018
url http://eprints.utm.my/id/eprint/101842/1/AidaAmiraZaliMSKE2018.pdf
http://eprints.utm.my/id/eprint/101842/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:145043
_version_ 1772811120894017536
score 13.211869

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