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邱天爽
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教授   博士生导师   硕士生导师

性别: 男

毕业院校: 大连理工大学

学位: 博士

所在单位: 生物医学工程学院

学科: 信号与信息处理. 生物医学工程

办公地点: 大连理工大学创新园大厦

联系方式: 电子邮箱:qiutsh@dlut.edu.cn; 电话:15898159801

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An efficient real-valued sparse Bayesian learning for non-circular signal's DOA estimation in the presence of impulsive noise

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论文类型: 期刊论文

发表时间: 2021-01-10

发表刊物: DIGITAL SIGNAL PROCESSING

卷号: 106

ISSN号: 1051-2004

关键字: DOA estimation; Impulsive noise; Sparse Bayesian learning; Real-valued; Non-circular signal

摘要: Currently, sparse Bayesian learning (SBL) has been introduced to solve direction of arrival (DOA) estimation in different situations. In the line of DOA estimation under impulsive noise, existing SBL-based methods need large computation which will restrict their practicabilities. To address this problem, we propose an efficient method based on a real-valued SBL for non-circular signals in this paper. Firstly, received signal model is transformed into a real-valued form using the characteristic of non-circular signals' structure. Then, a sparse representation of the modified signal model is constructed in the presence of impulsive noise. Finally, SBL is applied to reconstruct the real-valued sparse model and solve the DOAs estimation. A series of simulations are carried out in different conditions to evaluate the proposed method. Simulation results demonstrate that our method shows better performance than existing methods. (C) 2020 Elsevier Inc. All rights reserved.

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