Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform

Loran-C is the most essential backup and supplementary system for the global navigation satellite system (GNSS). Continuous wave interference (CWI) is one of the main interferences in the Loran-C system, which will cause errors in the measurement of the time of arrival, thereby affecting positioning...

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Autores principales:	Wenwen Ma, Jiuxiang Gao, Yanning Yuan, Zhensheng Shi, Xiaoli Xi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	Loran-C continuous wave interference wavelet transform discrete cosine transform morphological component analysis Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/eb37e29589734aed822ed3259ce19cdc
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spelling	oai:doaj.org-article:eb37e29589734aed822ed3259ce19cdc2021-11-11T19:08:58ZSuppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform10.3390/s212171531424-8220https://doaj.org/article/eb37e29589734aed822ed3259ce19cdc2021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7153https://doaj.org/toc/1424-8220Loran-C is the most essential backup and supplementary system for the global navigation satellite system (GNSS). Continuous wave interference (CWI) is one of the main interferences in the Loran-C system, which will cause errors in the measurement of the time of arrival, thereby affecting positioning performance. The traditional adaptive notch filter method needs to know the frequency of CWI when removing it, and the number is limited. This paper presents a method based on sparseness to suppress the CWI in the Loran-C signal. According to the different morphological characteristics of the Loran-C signal and the CWI, we construct dictionaries suitable for the two components, respectively. We use the tunable Q-factor wavelet transform and the discrete cosine transform to make the two components obtain a good sparse representation in their respective dictionaries. Then, the two components are separated using the morphological component analysis theory. We illustrate this method using both synthetic data and actual data. A huge advantage of the proposed method is that there is no need to know the frequencies of the CWI for it can better cope with frequency changes of the CWI in the actual environments. Compared with the adaptive notch filter method, the results of the proposed method show that our approach is more effective and convenient.Wenwen MaJiuxiang GaoYanning YuanZhensheng ShiXiaoli XiMDPI AGarticleLoran-Ccontinuous wave interferencewavelet transformdiscrete cosine transformmorphological component analysisChemical technologyTP1-1185ENSensors, Vol 21, Iss 7153, p 7153 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Loran-C continuous wave interference wavelet transform discrete cosine transform morphological component analysis Chemical technology TP1-1185
spellingShingle	Loran-C continuous wave interference wavelet transform discrete cosine transform morphological component analysis Chemical technology TP1-1185 Wenwen Ma Jiuxiang Gao Yanning Yuan Zhensheng Shi Xiaoli Xi Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
description	Loran-C is the most essential backup and supplementary system for the global navigation satellite system (GNSS). Continuous wave interference (CWI) is one of the main interferences in the Loran-C system, which will cause errors in the measurement of the time of arrival, thereby affecting positioning performance. The traditional adaptive notch filter method needs to know the frequency of CWI when removing it, and the number is limited. This paper presents a method based on sparseness to suppress the CWI in the Loran-C signal. According to the different morphological characteristics of the Loran-C signal and the CWI, we construct dictionaries suitable for the two components, respectively. We use the tunable Q-factor wavelet transform and the discrete cosine transform to make the two components obtain a good sparse representation in their respective dictionaries. Then, the two components are separated using the morphological component analysis theory. We illustrate this method using both synthetic data and actual data. A huge advantage of the proposed method is that there is no need to know the frequencies of the CWI for it can better cope with frequency changes of the CWI in the actual environments. Compared with the adaptive notch filter method, the results of the proposed method show that our approach is more effective and convenient.
format	article
author	Wenwen Ma Jiuxiang Gao Yanning Yuan Zhensheng Shi Xiaoli Xi
author_facet	Wenwen Ma Jiuxiang Gao Yanning Yuan Zhensheng Shi Xiaoli Xi
author_sort	Wenwen Ma
title	Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
title_short	Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
title_full	Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
title_fullStr	Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
title_full_unstemmed	Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform
title_sort	suppression of continuous wave interference in loran-c signal based on sparse optimization using tunable q-factor wavelet transform and discrete cosine transform
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/eb37e29589734aed822ed3259ce19cdc
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_version_	1718431619186950144

Suppression of Continuous Wave Interference in Loran-C Signal Based on Sparse Optimization Using Tunable Q-Factor Wavelet Transform and Discrete Cosine Transform

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