基于二级嵌套阵列的宽频段欠定波达方向估计
发布时间：2018-12-12 23:55
【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]:To solve the problem of (DOA) estimation of underdetermined direction of arrival (DOA) in broadband band, a DOA estimation method based on two-stage nested array is proposed. The spatial frequency is used to reduce the dimension of the array received data, the spatial frequency continuous sparse model is established by using the spatial sparsity of spatial frequency, and the high-resolution estimation of spatial frequency is obtained by using the original duality method and polynomial rooting. The covariance matrix in frequency domain is constructed and the eigenvalue is decomposed, and the pairing function is established by using the sum of large feature vectors to realize the accurate pairing of signal frequency and spatial frequency to obtain DOA estimation. The results show that the number of signals estimated by this method is much larger than the actual number of elements, and the influence of the model mismatch caused by the discretization of angle domain on the estimation performance can be effectively avoided in the traditional sparse reconstruction method. The estimation accuracy and resolution are improved.
【作者单位】： 解放军电子工程学院;
【基金】：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)
【分类号】：TN911.23
[Abstract]:To solve the problem of (DOA) estimation of underdetermined direction of arrival (DOA) in broadband band, a DOA estimation method based on two-stage nested array is proposed. The spatial frequency is used to reduce the dimension of the array received data, the spatial frequency continuous sparse model is established by using the spatial sparsity of spatial frequency, and the high-resolution estimation of spatial frequency is obtained by using the original duality method and polynomial rooting. The covariance matrix in frequency domain is constructed and the eigenvalue is decomposed, and the pairing function is established by using the sum of large feature vectors to realize the accurate pairing of signal frequency and spatial frequency to obtain DOA estimation. The results show that the number of signals estimated by this method is much larger than the actual number of elements, and the influence of the model mismatch caused by the discretization of angle domain on the estimation performance can be effectively avoided in the traditional sparse reconstruction method. The estimation accuracy and resolution are improved.
【作者单位】： 解放军电子工程学院;
【基金】：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)
【分类号】：TN911.23
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