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Single-Snapshot Time-Domain Direction of Arrival Estimation under Bayesian Group-Sparse Hypothesis and Vector Sensor Antennas

机译:贝叶斯稀疏假设和矢量传感器天线下单快照时域到达估计的方向

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In this work, an optimal single-snapshot, time domain, group-sparse optimal Bayesian DOA estimation method is proposed and tested on a vector sensors antenna system. Exploiting the group-sparse property of the DOA and the Bayesian formulation of the estimation problem, we provide a fast and accurate DOA estimation algorithm. The proposed estimation method can be used for different steering matrix formulations since the optimal standardization matrix is computed directly from the knowledge of the steering matrix and noise covariance matrix Thanks to this, the algorithm does not requires any kind of calibration or human supervision to operate correctly. In the following, we propose the theoretical basis and details about the estimation algorithm and a possible implementation based on FISTA followed by the results of our computer simulations test.
机译:在这项工作中,提出了一种最佳的单快照,时域,组稀疏的最佳贝叶斯DOA估计方法,并在矢量传感器天线系统上进行了测试。利用DOA的群稀疏性质和估计问题的贝叶斯公式,我们提供了一种快速而准确的DOA估计算法。由于直接从转向矩阵和噪声协方差矩阵的知识直接计算出最佳标准化矩阵,因此所建议的估计方法可用于不同的转向矩阵公式,这使得该算法不需要任何类型的校准或人工监督即可正确运行。在下文中,我们提出了有关估计算法的理论基础和细节,并提出了基于FISTA的可能实现方法,然后给出了计算机模拟测试的结果。

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