Correntropy-based DOA estimation algorithm under impulsive noise environments
In this paper, the direction of arrival (DOA) estimation of signals in the presence of impulsive noise environment is studied. Complex isotropic symmetric alpha-stable ( SαS ) random variables are modeled as impulsive noise, then a novel second-order statistic method that correntropy-based covarianc...
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Published in | EURASIP journal on wireless communications and networking Vol. 2020; no. 1; pp. 1 - 20 |
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Main Authors | , |
Format | Journal Article |
Language | English |
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28.07.2020
Springer Nature B.V SpringerOpen |
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Abstract | In this paper, the direction of arrival (DOA) estimation of signals in the presence of impulsive noise environment is studied. Complex isotropic symmetric alpha-stable (
SαS
) random variables are modeled as impulsive noise, then a novel second-order statistic method that correntropy-based covariance matrix (CBCM) is defined, based on the combination of the CBCM of the array sensor outputs with the signal subspace technique (e.g., multiple signal classification (MUSIC)), which can be achieved source localization under impulsive noise environments. The Monte-Carlo simulation results illustrate the improved performance of CBCM-MUSIC for DOA estimation under a wide range of impulsive noise conditions. |
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AbstractList | In this paper, the direction of arrival (DOA) estimation of signals in the presence of impulsive noise environment is studied. Complex isotropic symmetric alpha-stable (
SαS
) random variables are modeled as impulsive noise, then a novel second-order statistic method that correntropy-based covariance matrix (CBCM) is defined, based on the combination of the CBCM of the array sensor outputs with the signal subspace technique (e.g., multiple signal classification (MUSIC)), which can be achieved source localization under impulsive noise environments. The Monte-Carlo simulation results illustrate the improved performance of CBCM-MUSIC for DOA estimation under a wide range of impulsive noise conditions. In this paper, the direction of arrival (DOA) estimation of signals in the presence of impulsive noise environment is studied. Complex isotropic symmetric alpha-stable (SαS) random variables are modeled as impulsive noise, then a novel second-order statistic method that correntropy-based covariance matrix (CBCM) is defined, based on the combination of the CBCM of the array sensor outputs with the signal subspace technique (e.g., multiple signal classification (MUSIC)), which can be achieved source localization under impulsive noise environments. The Monte-Carlo simulation results illustrate the improved performance of CBCM-MUSIC for DOA estimation under a wide range of impulsive noise conditions. Abstract In this paper, the direction of arrival (DOA) estimation of signals in the presence of impulsive noise environment is studied. Complex isotropic symmetric alpha-stable (SαS) random variables are modeled as impulsive noise, then a novel second-order statistic method that correntropy-based covariance matrix (CBCM) is defined, based on the combination of the CBCM of the array sensor outputs with the signal subspace technique (e.g., multiple signal classification (MUSIC)), which can be achieved source localization under impulsive noise environments. The Monte-Carlo simulation results illustrate the improved performance of CBCM-MUSIC for DOA estimation under a wide range of impulsive noise conditions. |
ArticleNumber | 154 |
Author | Chen, Jin Guan, Sheng |
Author_xml | – sequence: 1 givenname: Jin orcidid: 0000-0002-3707-7779 surname: Chen fullname: Chen, Jin email: cjwoods@163.com organization: Tianjin Key Laboratory of Wireless Communications and Power Transmission, Tianjin Normal University – sequence: 2 givenname: Sheng surname: Guan fullname: Guan, Sheng email: gs-sunny@foxmail.com organization: Tianjin Key Laboratory of Wireless Communications and Power Transmission, Tianjin Normal University |
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CitedBy_id | crossref_primary_10_3390_electronics13122386 crossref_primary_10_1016_j_dsp_2023_104254 crossref_primary_10_1109_TGRS_2024_3509864 crossref_primary_10_1109_TVT_2020_3044994 crossref_primary_10_1109_TVT_2022_3184385 crossref_primary_10_1109_OJSP_2024_3360896 crossref_primary_10_1109_TAES_2023_3275934 crossref_primary_10_1109_TVT_2023_3349026 |
Cites_doi | 10.1109/ACCESS.2017.2763599 10.1016/j.adhoc.2016.12.007 10.1109/TPAMI.2010.220 10.1109/TAP.1986.1143830 10.1109/TSP.2006.872524 10.1109/JSEN.2016.2526686 10.1016/j.sigpro.2014.04.033 10.1109/MCOM.2017.1600400 10.1109/78.510611 10.1002/j.1538-7305.1974.tb02791.x 10.1109/LSP.2009.2031716 10.1016/j.sigpro.2006.12.015 10.1109/49.233212 10.1109/TSP.2010.2043976 10.1109/78.934131 10.1109/JSAC.2013.130214 10.1109/TSP.2007.896065 10.1109/78.942634 10.1109/TAP.2013.2256093 10.1109/TVT.2002.1002503 10.1109/PIMRC.2002.1047300 |
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SubjectTerms | Algorithms Communications Engineering Complex isotropic symmetric alpha-stable Computer simulation Correntropy Covariance matrix Direction of arrival Engineering Information Systems Applications (incl.Internet) Monte Carlo simulation Networks Noise Radar and Sonar Networks Random variables Sensor arrays Signal classification Signal,Image and Speech Processing |
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Title | Correntropy-based DOA estimation algorithm under impulsive noise environments |
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