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DOA and Polarization Estimation Using an Electromagnetic Vector Sensor Uniform Circular Array Based on the ESPRIT Algorithm.
Wu, Na; Qu, Zhiyu; Si, Weijian; Jiao, Shuhong.
Afiliação
  • Wu N; Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. wunahmc@163.com.
  • Qu Z; Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. quzhiyu@hrbeu.edu.cn.
  • Si W; Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. swj0418@263.net.
  • Jiao S; Department of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China. jiaoshuhong@hrbeu.edu.cn.
Sensors (Basel) ; 16(12)2016 Dec 13.
Article em En | MEDLINE | ID: mdl-27983584
ABSTRACT
In array signal processing systems, the direction of arrival (DOA) and polarization of signals based on uniform linear or rectangular sensor arrays are generally obtained by rotational invariance techniques (ESPRIT). However, since the ESPRIT algorithm relies on the rotational invariant structure of the received data, it cannot be applied to electromagnetic vector sensor arrays (EVSAs) featuring uniform circular patterns. To overcome this limitation, a fourth-order cumulant-based ESPRIT algorithm is proposed in this paper, for joint estimation of DOA and polarization based on a uniform circular EVSA. The proposed algorithm utilizes the fourth-order cumulant to obtain a virtual extended array of a uniform circular EVSA, from which the pairs of rotation invariant sub-arrays are obtained. The ESPRIT algorithm and parameter pair matching are then utilized to estimate the DOA and polarization of the incident signals. The closed-form parameter estimation algorithm can effectively reduce the computational complexity of the joint estimation, which has been demonstrated by numerical simulations.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2016 Tipo de documento: Article