Underdetermined wideband DOA estimation of off-grid sources employing the difference co-array concept

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• 作者：Qing Shen^a ; ^{qing-shen@outlook.com" class="auth_mail" title="E-mail the corresponding author} ; Wei Cui^a ; ^{cuiwei@bit.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Wei Liu^b ; ^{w.liu@sheffield.ac.uk" class="auth_mail" title="E-mail the corresponding author} ; Siliang Wu^a ; ^{siliangw@bit.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Yimin D. Zhang^c ; ^{ydzhang@temple.edu" class="auth_mail" title="E-mail the corresponding author} ; Moeness G. Amin^d ; ^{moeness.amin@villanova.edu" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Off-Grid ; Difference co-array ; Group sparsity ; DOA estimation ; Compressive sensing
• 刊名：Signal Processing
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：130
• 期：Complete
• 页码：299-304
• 全文大小：466 K

文摘

A wideband off-grid model is proposed to represent dictionary mismatch under the compressive sensing framework exploiting difference co-arrays. A group sparsity based off-grid method is proposed for underdetermined wideband direction of arrival (DOA) estimation which provides improved performance over the existing group sparsity based method with a same search grid. A two-step approach is then proposed which achieves an even better performance with significantly reduced computational complexity.