Reduced-Complexity Maximum Likelihood Direction-of-Arrival Estimation Based on Spatial Aliasing
Reduced-Complexity Maximum Likelihood Direction-of-Arrival Estimation Based on Spatial Aliasing
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DOI：
10.1109/tsp.2014.2367454
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发表时间：
2014-11
影响因子：
5.4
通讯作者：
Jong-Woo Shin;Young-Jun Lee;Hyoung-Nam Kim
中科院分区：
文献类型：
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作者：
Jong-Woo Shin;Young-Jun Lee;Hyoung-Nam Kim
空间混叠是一种不良现象，它阻碍了阵列信号处理中对撞击信号的到达方向 (DOA) 的唯一确定。然而，产生模糊 DOA 的空间混叠特性也可用于降低最大似然 (ML) DOA 估计中的计算复杂性。本文提出了一种结构方法，利用具有双倍缩放孔径的嵌套阵列结构生成的空间混叠来显着降低 ML DOA 估计的计算复杂性。 ML全网格搜索通过高度压缩的搜索范围和基于空间混叠导出的少量待搜索候选值在计算上得到简化。基于理论界限和计算机模拟计算复杂度的性能分析表明，与采用均匀线性阵列（ULA）的传统ML DOA估计相比，所提出的方法需要极大减少计算量，同时由于扩大的阵列孔径而实现估计精度的性能增强。
Spatial aliasing is an undesirable phenomenon that prevents the unique determination of the direction of arrival (DOA) of impinging signals in array signal processing. However, the characteristics of spatial aliasing that generates ambiguous DOAs can be also used to reduce the computational complexity in maximum-likelihood (ML) DOA estimation. This paper proposes a structural method to dramatically reduce the computational complexity of the ML DOA estimation using the spatial aliasing generated by a nested array structure with a doubly scaled aperture. An ML full grid search is computationally simplified by the highly compressed searching range and the small number of candidate values to be searched which are derived based on spatial aliasing. Performance analyses based on the theoretical bounds and computational complexity with computer simulations show that the proposed method requires an extremely reduced computational load compared to the conventional ML DOA estimation with a uniform linear array (ULA) while achieving the performance enhancement in the estimation accuracy due to the enlarged array aperture.