改进的变分稀疏贝叶斯学习离格DOA估计方法

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振动与冲击 ›› 2024, Vol. 43 ›› Issue (13) : 134-143.

论文

王绪虎1，金序1，侯玉君1，徐振华2，田雨1，张群飞3

作者信息 +

Improved variational sparse Bayesian learning off-grid DOA estimation method

WANG Xuhu1, JIN Xu1, HOU Yujun1, XU Zhenhua2, TIAN Yu1, ZHANG Qunfei3

Author information +

文章历史 +

摘要

为提高阵列信号处理运算速率，改善其方位估计性能，提出了一种改进变分稀疏贝叶斯学习离格DOA估计方法。该方法利用实值变换，将向量化后的接收信号协方差矩阵转化到实数域，结合变分稀疏贝叶斯学习和网格演化的思想，在迭代过程中使网格从初始的均匀网格自适应地演化为非均匀网格，通过网格更新和网格裂变交替迭代使演化后的网格点逐渐逼近真实信源方位。仿真结果表明，改进方法与传统压缩感知类方法相比，减小了运算量，提高了运算速率，且具有更高的方位估计精度和方位分辨能力，在少快拍和低信噪比情况下，改进方法性能提升的优势更明显。湖上试验数据处理结果进一步验证了该方法的有效性和工程实用性。

Abstract

In order to improve the processing speed and direction-of-arrival (DOA) estimation performance of array signal, an improved variational sparse Bayesian learning method for off-grid DOA estimation is proposed. The real-value transformation is utilized in this method, by which the signal of the vectorized covariance matrix in the complex domain is transformed into the real domain. Combining the ideas of variational sparse Bayesian learning and grid evolution, the grid can adaptively evolve from the initial uniform grid to the non-uniform grid during the iteration process, whereby the evolved grid points gradually approximate the real source orientation through alternate iterations of grid update and grid fission. Compared with the traditional compression sensing methods, the simulation results of the proposed method not only decrease operation and improve the efficiencies of the operations but also have higher estimation accuracy and resolution of DOA. Especially in the case of fewer snapshots and the low signal-to-noise ratio (SNR), these advantages become more evident. The effectiveness and engineering practicality of the proposed method can be further verified by the data processing results of the on-lake experiments.

导出引用

王绪虎1，金序1，侯玉君1，徐振华2，田雨1，张群飞3. 改进的变分稀疏贝叶斯学习离格DOA估计方法[J]. 振动与冲击, 2024, 43(13): 134-143

WANG Xuhu1, JIN Xu1, HOU Yujun1, XU Zhenhua2, TIAN Yu1, ZHANG Qunfei3. Improved variational sparse Bayesian learning off-grid DOA estimation method[J]. Journal of Vibration and Shock, 2024, 43(13): 134-143

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