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Low Complexity DOA Estimation for Wideband Off-Grid Sources Based on Re-Focused Compressive Sensing With Dynamic Dictionary

机译:基于动态字典重压缩感知的宽带离网源低复杂度DOA估计

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摘要

Under the compressive sensing (CS) framework, a novel focusing based direction of arrival (DOA) estimation method is first proposed for wideband off-grid sources, and by avoiding the application of group sparsity (GS) across frequencies of interest, significant complexity reduction is achieved with its computational complexity close to that of solving a single frequency based direction finding problem. To further improve the performance by alleviating both the off-grid approximation errors and the focusing errors which are even worse for the off-grid case, a dynamic dictionary based re-focused off-grid DOA estimation method is developed with the number of extremely sparse grids involved in estimation refined to the number of detected sources, and thus the complexity is still very low due to the limited complexity increase introduced by iterations, while improved performance can be achieved compared with those fixed dictionary based off-grid methods.
机译:在压缩感知(CS)框架下,首先针对宽带离网源提出了一种新颖的基于聚焦的到达方向(DOA)估计方法,并且避免了在感兴趣的频率上应用组稀疏性(GS),从而显着降低了复杂度通过其计算复杂度接近于解决基于单个频率的测向问题的计算复杂度而实现了这一点。为了通过减轻离网近似误差和聚焦误差而进一步提高性能,对于离网情况更严重的是,开发了一种基于动态字典的重新聚焦离网DOA估计方法,该方法极少估计中涉及的网格细化到检测到的源的数量,并且由于迭代引入的有限的复杂度增加,因此复杂度仍然非常低,而与那些基于固定字典的离网方法相比,可以提高性能。

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