基于模式空间算法的声源二维DOA估计

针对传统高分辨率谱估计法估计远场声源波达方向（direction of arrival, DOA）时计算量大、对相干信号估计失准的问题，本文提出一种改进的基于圆形麦克风阵列和四阶累积量的声源二维DOA估计算法。该算法结合了圆阵定位无死角的优势和矩阵虚拟扩展获得更多声源定位信息的长处。首先利用模式空间变换将均匀圆形阵列（UCA）虚拟化成2K+1个均匀线性阵列（ULA），并应用空间平滑技术将虚拟线性阵列划分成L个子阵；接着利用四阶累积构造方法提取有效阵元信息并去掉冗余数据，通过重构矩阵得到新的接收数据；最后通过Music-like算法搜索谱峰获得声源信号的方位角和俯仰角。仿真结果表明，在信噪比较低时，相比传统的高分辨谱估计算法，本文算法可实现对远场相干信号的高精度估计；同时本文算法也具有更低的均方根误差性能，且能有效减少运行时间。

Two-Dimensional DOA Estimation of Sound Source Based on Mode Space Algorithm

In order to solve the problem that the traditional high resolution spectral estimation methods estimate the direction of arrival (DOA) of far field sound source with large computation and inaccurate estimation of coherent signals, a two-dimensional DOA estimation method based on circular microphone array and fourth-order cumulant is proposed. The algorithm combines the advantages of circular array location without dead angle and matrix virtual extension to obtain more information of sound source location. Firstly, the uniform circular array (UCA) is virtualized into 2K+1 uniform linear array (ULA) by means of pattern space transformation, and the virtual linear array is divided into L subarrays by space smoothing technology. Then the fourth order cumulative construction method is used to extract the effective matrix information and remove the redundant data. Finally, the azimuth and pitch angles of the acoustic source signal are obtained by the Music-like algorithm. The simulation results show that the proposed algorithm can achieve high-precision estimation of far field coherent signals compared with traditional high-resolution spectral estimation algorithms when the signal-to-noise ratio is low. At the same time, the algorithm also has lower root mean square error performance and can effectively reduce the running time.