Wideband Direction-of-Arrival Estimation Based on Hierarchical Sparse Bayesian Learning for Signals with the Same or Different Frequency Bands
Wideband Direction-of-Arrival Estimation Based on Hierarchical Sparse Bayesian Learning for Signals with the Same or Different Frequency Bands
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DOI：
10.3390/electronics12051123
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发表时间：
2023-02
期刊：
影响因子：
2.9
通讯作者：
Yixin Yang;Yahao Zhang;Long Yang;Yong Wang
中科院分区：
文献类型：
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作者：
Yixin Yang;Yahao Zhang;Long Yang;Yong Wang
基于联合稀疏性的宽带稀疏贝叶斯学习算法在信号共享频带时具有较高的波达方向估计精度。然而，当信号频带不重叠或部分重叠时，即，频带是不同的，该方法的性能由于不适当的先验信号而降低。本文旨在将WSBL扩展到更一般的版本，它也适用于信号频带不重叠或部分重叠的情况。假定信号在空间中稀疏分布，则其列由每个频率点中的信号组成的信号矩阵是行稀疏的。此外，当信号占用不同的频带时，某些频率点上的信号向量具有不同的稀疏支持。因此，分层稀疏先验被分配给信号矩阵，其中一组超参数用于确保行稀疏性，另一组用于调整每个频率点中的信号稀疏性。最后在贝叶斯框架下估计到达角。仿真结果表明，该方法在相同频段和不同频段情况下均具有较好的估计精度。
Wideband sparse Bayesian learning (WSBL) based on joint sparsity achieves high direction-of-arrival (DOA) estimation precision when the signals share the same frequency band. However, when the signal frequency bands are non-overlapped or partially overlapped, i.e., the frequency bands are different, the performance of the method degrades due to the improper prior on signal. This paper aims at extending the WSBL to a more general version, which is also suitable for the cases where the signal frequency bands are non-overlapped or partially overlapped. Given that the signals are sparsely distributed in the space, the signal matrix whose column is composed of the signal in each frequency bin is row-sparse. Moreover, the signal vectors in some frequency bins have different sparse supports when the signals occupy the different frequency bands. Therefore, a hierarchical sparse prior is assigned to the signal matrix, where a set of hyperparameters are used to ensure the row-sparsity and the other set are used to adjust the signal sparsity in each frequency bin. The DOAs are finally estimated in the Bayesian framework. The simulation results verify that the proposed method achieves good performance on estimation precision in both the same and different frequency band scenarios.