Off-grid DOA estimation of correlated sources for nonuniform linear array through hierarchical sparse recovery in a Bayesian framework and asymptotic minimum variance criterion
Off-grid DOA estimation of correlated sources for nonuniform linear array through hierarchical sparse recovery in a Bayesian framework and asymptotic minimum variance criterion
复制标题
通过贝叶斯框架中的分层稀疏恢复和渐近最小方差准则对非均匀线性阵列相关源进行离网 DOA 估计
DOI：
10.1016/j.sigpro.2020.107813
复制
发表时间：
2021-01
影响因子：
4.4
通讯作者：
Wang Yong
中科院分区：
文献类型：
--
作者：
Zhang Yahao;Yang Yixin;Yang Long;Wang Yong
提出了一种基于分层稀疏恢复和渐近最小方差（AMV）准则的非均匀线阵（NLA）相关信源条件下的离网波达方向（DOA）估计方法。该方法首先将空间划分为离散网格。在此网格上建模的信号协方差矩阵的大多数行和列都是零向量，因为源的数量远远小于网格点的数量。因此，矢量化的信号协方差矩阵被视为块稀疏向量，并且活动块是稀疏向量。在此基础上，一个分层的稀疏先验分配的矢量化信号协方差矩阵，以鼓励块之间和块内的稀疏性。最后，变分贝叶斯推断被应用于估计向量化的信号协方差矩阵。此外，一阶泰勒级数展开被施加到近似的导向矢量的真实波达方向和最近的网格点之间的网格误差的函数。根据AMV准则估计网格误差，并应用于迭代修改网格，从而减轻基失配。仿真结果表明，该方法在NLA相关源条件下具有较高的估计精度。
This paper provides a method to solve off-grid direction-of-arrival (DOA) estimation for nonuniform linear array (NLA) correlated source condition through hierarchical sparse recovery and asymptotic minimum variance (AMV) criterion. In this method, space is firstly divided into a discretized grid. Most rows and columns of the signal covariance matrix modeled on this grid are zero vectors because the number of sources is considerably smaller than that of grid points. Hence, the vectorized signal covariance matrix is regarded as a block-sparse vector, and active blocks are sparse vectors. Based on this, a hierarchical sparse prior is then assigned on the vectorized signal covariance matrix to encourage the sparsity between and within blocks. Finally, the variational Bayesian inference is applied to estimate the vectorized signal covariance matrix. Furthermore, first-order Taylor series expansion is applied to approximate the steering vector as a function of the grid error between the true DOA and the closest grid point. Grid error is estimated under the AMV criterion and applied to modify the grid iteratively, thus alleviating the basis mismatch. Simulation results show that the proposed method achieves high estimation accuracy for the NLA correlated source condition.
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影响因子：
5.4
作者：
Zheng, Jimeng;Kaveh, Mostafa
通讯作者：
Kaveh, Mostafa
求解稀疏阵列DOA估计问题的变分贝叶斯策略
影响因子：
2.9
作者：
Yang Jie;Yang Yixin;Lu Jieyi
通讯作者：
Lu Jieyi
离网到达方向估计的根稀疏渐近最小方差
影响因子：
4.4
作者：
Zhang Yahao;Yang Yixin;Yang Long;Guo Xijing
通讯作者：
Guo Xijing
两种基于稀疏的离网到达方向估计方法
影响因子：
4.4
作者：
Wu Xiaohuan;Zhu Wei-Ping;Yan Jun;Zhang Zeyun
通讯作者：
Zhang Zeyun
DOI：
10.1109/78.757219
发表时间：
1999-05
期刊：
IEEE Trans. Signal Process.
影响因子：
--
作者：
Hongbin Li;P. Stoica;Jian Li
通讯作者：
Hongbin Li;P. Stoica;Jian Li