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浙江大学学报(工学版)
自动化技术     
基于二级嵌套阵列的宽频段欠定波达方向估计
吴晨曦, 张旻, 王可人
解放军电子工程学院,安徽 合肥 230037
Broadband underdetermined direction of arrival estimation based on two level nested array
WU Chen-xi, ZHANG Min, WANG Ke-ren
Electronic Engineering Institute of PLA, Hefei, 230037, China
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摘要:

针对宽频段欠定波达方向(DOA)估计问题,提出基于二级嵌套阵列的DOA估计方法.利用空间频率对阵列接收数据进行降维处理;利用空间频率的空域稀疏性建立空间频率连续稀疏模型,利用原始对偶方法以及多项式求根得到空间频率的高分辨估计;构建频域协方差矩阵并进行特征分解,利用大特征矢量之和来建立配对函数实现信号频率与空间频率准确配对得到DOA估计.结果表明,该方法可估计的信号数远大于实际阵元数,同时能够有效避免传统稀疏重构方法中由于角度域离散化所导致的模型不匹配对估计性能的影响,提高了估计精度与分辨力.

Abstract:

A novel broadband direction of arrival (DOA) estimation algorithm based on two level nested array was proposed to achieve broadband underdetermined DOA estimation. The dimension of the array received data was reduced by using spatial frequencies. Spatial frequencies continuous sparse recovery model was constructed by using the spatial sparseness of the spatial frequency. The high resolution estimation of spatial frequencies was achieved with primal dual approach and root finding. The frequency domain covariance matrix was constructed.The spatial frequencies and frequencies were matched by using the sparse recovery of the sum of larger eigenvectors, which are coming from the frequency domain covariance matrix’s eigen value decomposition(ED).Then DOA estimation can be obtained.Results show that the number of sources by the proposed algorithm is larger than the number of actual sensors. Off-grid effects caused by discretizing this range onto a grid in traditional sparse recovery can be neglected, thus improving precision and resolution of DOA estimation.

出版日期: 2017-05-01
CLC:  TN 911.23  
基金资助:

国家自然科学基金资助项目(61171170);安徽省自然科学基金资助项目(1408085QF115).

作者简介: 吴晨曦(1988—),男,博士生,从事阵列信号处理方面等研究. ORCID: 0000-0003-4960-4932. E-mail:wuchenxi19881201@126.com
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引用本文:

吴晨曦, 张旻, 王可人. 基于二级嵌套阵列的宽频段欠定波达方向估计[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2017.05.023.

WU Chen-xi, ZHANG Min, WANG Ke-ren. Broadband underdetermined direction of arrival estimation based on two level nested array. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2017.05.023.

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