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Direction-of-arrival estimation based on joint diagonalization of matrices in different direct-to-reverberation ratios

机译:基于不同直接混响比的矩阵联合对角线化的到达方向估计

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摘要

Direction-of-arrival (DOA) estimation is very important in many applications. The MUltiple SIgnal Classification (MUSIC) algorithm is one of the well-known methods of DOA estimation. However, in a real environment with reverberation, MUSIC's estimation accuracy is degraded. In this paper, we propose an improved MUSIC algorithm by using joint diagonalization of the covariance matrices of two different direct-to-reverberation ratio (DRR) periods corresponding to higher and lower DRR periods in a short time. In addition, we also introduce a method for detecting different DRR periods by using peak-hold processing for our proposed method. Computer simulations verified that the proposed method improves the accuracy of the azimuth in DOA estimation compared with the conventional method for both simulated and actual impulse responses.
机译:到达方向(DOA)估计在许多应用中非常重要。多元信号分类(MUSIC)算法是DOA估计的众所周知的方法之一。但是,在具有混响的真实环境中,MUSIC的估计精度会下降。在本文中,我们提出了一种改进的MUSIC算法,该方法通过在短时间内将两个不同的直接混响比(DRR)周期对应于较高和较低的DRR周期的协方差矩阵进行联合对角化来实现。此外,我们还介绍了一种通过使用峰值保持处理来检测不同DRR周期的方法。计算机仿真结果表明,与常规方法相比,该方法可以提高DOA估计中方位角的精度。

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