DOA estimation of multiple sources in sparse space with an extended array technique

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• 作者：Penghao Xu ; Bing Yan ; Shouwei Hu
• 关键词：Direction of arrival ; Virtual element ; Extended array ; Singular value decomposition
• 刊名：Cluster Computing
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：19
• 期：3
• 页码：1437-1447
• 全文大小：1,090 KB
• 刊物类别：Computer Science
• 刊物主题：Processor Architectures
  Operating Systems
  Computer Communication Networks
  
• 出版者：Springer Netherlands
• ISSN：1573-7543
• 卷排序：19

文摘

An algorithm to improve direction of arrival (DOA) estimation accuracy with an extended sensor array in the presence of multiple coherent signal sources is proposed. The algorithm uses virtual element theory to extend the sensor array, estimates virtual element information via linear prediction and expands the array aperture in practical sense; the sparsity of the target orientation in angle space is exploited to establish an over-complete dictionary and a reception model for the array signal in sparse space; the received array data is preprocessed using singular value decomposition (SVD) method and target DOA estimation is realized by calculating the best atoms. The algorithm improves DOA estimation accuracy by extended array and uses SVD to control computational complexity effectively, which ensures the accuracy and efficiency. Computer simulation shows that the proposed algorithm is able to accurately estimate the DOA for both single-target and closely spaced multi-target cases in low signal-to-noise ratio environments, and also has excellent DOA estimation performance in the presence of multiple coherent signal sources.