DOA estimation based on mode and maximum eigenvector algorithm with reverberation environment

Hengyi Liu, Zhenghong Liu, Linxia Su, Liyan Luo
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Abstract

To solve the problem of coherent sound source direction of arrival (DOA) estimation of microphone uniform circular array in indoor reverberation environment, an improved MUSIC algorithm for microphone uniform circular array (UCA) is proposed. The pre-processing uses the mode space to change into several virtual uniform linear arrays. The maximum feature vector matrix is constructed by decomposing the covariance matrix of the snapshot data. The information of all sound sources is used, and the covariance matrix is also restored to the diagonal matrix, which greatly reduces the error caused by the pre-processing. The spatial spectral function is obtained, and the spectral function is searched to obtain N directions and pitch angles corresponding to N signals. The MATLAB tool is used to simulate the indoor reverberation environment microphone uniform ring array model and the improved MUSIC algorithm. The simulation results show that the algorithm has better estimation accuracy for indoor sound sources under ideal conditions, and has higher resolution and lower signal-to-noise ratio.
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基于混响环境下模式和最大特征向量算法的 DOA 估计
为解决室内混响环境下传声器均匀圆形阵列的相干声源到达方向(DOA)估计问题,提出了一种改进的传声器均匀圆形阵列(UCA)MUSIC 算法。预处理利用模式空间转换为多个虚拟均匀线性阵列。通过分解快照数据的协方差矩阵来构建最大特征向量矩阵。利用所有声源的信息,同时将协方差矩阵还原为对角矩阵,大大减少了预处理带来的误差。获得空间谱函数,并搜索谱函数以获得 N 个信号对应的 N 个方向和俯仰角。利用 MATLAB 工具对室内混响环境麦克风均匀环形阵模型和改进的 MUSIC 算法进行仿真。仿真结果表明,该算法在理想条件下对室内声源的估计精度更高,分辨率更高,信噪比更低。
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