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UNI-VECTOR-SENSOR DIRECTION FINDING WITH REGULARIZED ESPRIT

UNI-VECTOR-SENSOR DIRECTION FINDING WITH REGULARIZED ESPRIT
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摘要 The regularized Least-Squares Estimation method of Signal Parameters via Rotational Invariance Techniques (LS-ESPRIT) is herein proposed for Direction-Of-Arrival (DOA) estimation of non-Gaussian sources with only one acoustic vector-sensor. The Second-Order Statistics (SOS) and Higher-Order Statistics (HOS) of data are fused within a regularization framework. The steering vectors can be blindly identified by the regularized ESPRIT, from which the aim of DOA estimation can be achieved. Several variants of the regularized ESPRIT are discussed. A suboptimal scheme for deter- mination of the regularization parameters is also given. The regularized Least-Squares Estimation method of Signal Parameters via Rotational Invariance Techniques (LS-ESPRIT) is herein proposed for Direction-Of-Arrival (DOA) estimation of non-Gaussian sources with only one acoustic vector-sensor. The Second-Order Statistics (SOS) and Higher-Order Statistics (HOS) of data are fused within a regularization framework. The steering vectors can be blindly identified by the regularized ESPRIT, from which the aim of DOA estimation can be achieved. Several variants of the regularized ESPRIT are discussed. A suboptimal scheme for determination of the regularization parameters is also given.
出处 《Journal of Electronics(China)》 2008年第1期20-27,共8页 电子科学学刊(英文版)
基金 Supported by the University Basic Research Foundation of Beijing Institute of Technology (No.BIT-UBF- 200501F4202).
关键词 矢量敏感器 DOA HOS 通讯系统 Direction-Of-Arrival (DOA) estimation Vector-sensor Higher-Order Statistics (HOS)
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参考文献10

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