Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework

Aiming at the problems of low precision and high computational complexity in estimating coherent signals by traditional polarization sensitive array, a joint parameter estimation algorithm based on sparse Bayesian learning framework for direction of arrival and polarization information is proposed.F...

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Autor principal:	Xu Haifeng
Formato:	article
Lenguaje:	ZH
Publicado:	Editorial Office of Aero Weaponry 2021
Materias:	\|polarization sensitive array\|joint parameter estimation\|sparse bayesian learning\|modulus constraint\|unitary transformation Motor vehicles. Aeronautics. Astronautics TL1-4050
Acceso en línea:	https://doaj.org/article/285b344fe364402cb3093161fba50fc5
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id	oai:doaj.org-article:285b344fe364402cb3093161fba50fc5
record_format	dspace
spelling	oai:doaj.org-article:285b344fe364402cb3093161fba50fc52021-11-30T00:13:49ZJoint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework1673-504810.12132/ISSN.1673-5048.2019.0090https://doaj.org/article/285b344fe364402cb3093161fba50fc52021-04-01T00:00:00Zhttps://www.aeroweaponry.avic.com/fileup/1673-5048/PDF/1623391885786-1218833045.pdfhttps://doaj.org/toc/1673-5048Aiming at the problems of low precision and high computational complexity in estimating coherent signals by traditional polarization sensitive array, a joint parameter estimation algorithm based on sparse Bayesian learning framework for direction of arrival and polarization information is proposed.Firstly, the observation matrix is obtained by sparse data receiving matrix, then the observation data matrix is transformed from complex domain to real domain by unitary transformation, and a three-layer sparse prior is applied to the model parameters.Then, according to the variational Bayesian theory, the power spectrum function of sparse signal is constructed by the mean and variance of the model parameters, and the DOA of the signal is obtained by peak search. Finally, the estimated signal DOA and modulus constraint are used to obtain the polarization information. The simulation results show that the proposed algorithm can correctly locate coherent incident signals, and has higher direction finding accuracy and lower computational complexity.Xu HaifengEditorial Office of Aero Weaponryarticle\|polarization sensitive array\|joint parameter estimation\|sparse bayesian learning\|modulus constraint\|unitary transformationMotor vehicles. Aeronautics. AstronauticsTL1-4050ZHHangkong bingqi, Vol 28, Iss 2, Pp 113-118 (2021)
institution	DOAJ
collection	DOAJ
language	ZH
topic	\|polarization sensitive array\|joint parameter estimation\|sparse bayesian learning\|modulus constraint\|unitary transformation Motor vehicles. Aeronautics. Astronautics TL1-4050
spellingShingle	\|polarization sensitive array\|joint parameter estimation\|sparse bayesian learning\|modulus constraint\|unitary transformation Motor vehicles. Aeronautics. Astronautics TL1-4050 Xu Haifeng Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
description	Aiming at the problems of low precision and high computational complexity in estimating coherent signals by traditional polarization sensitive array, a joint parameter estimation algorithm based on sparse Bayesian learning framework for direction of arrival and polarization information is proposed.Firstly, the observation matrix is obtained by sparse data receiving matrix, then the observation data matrix is transformed from complex domain to real domain by unitary transformation, and a three-layer sparse prior is applied to the model parameters.Then, according to the variational Bayesian theory, the power spectrum function of sparse signal is constructed by the mean and variance of the model parameters, and the DOA of the signal is obtained by peak search. Finally, the estimated signal DOA and modulus constraint are used to obtain the polarization information. The simulation results show that the proposed algorithm can correctly locate coherent incident signals, and has higher direction finding accuracy and lower computational complexity.
format	article
author	Xu Haifeng
author_facet	Xu Haifeng
author_sort	Xu Haifeng
title	Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
title_short	Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
title_full	Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
title_fullStr	Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
title_full_unstemmed	Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework
title_sort	joint estimation for doa and polarization parameters in sparse bayesian framework
publisher	Editorial Office of Aero Weaponry
publishDate	2021
url	https://doaj.org/article/285b344fe364402cb3093161fba50fc5
work_keys_str_mv	AT xuhaifeng jointestimationfordoaandpolarizationparametersinsparsebayesianframework
_version_	1718406851583803392

Joint Estimation for DOA and Polarization Parameters in Sparse Bayesian Framework

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