利用块稀疏特性的压缩感知麦克风阵列声源定位

Microphone Array Direction of Arrival Estimation Based on Block Sparse Feature

与传统声源定位算法如相位变换加权、时延累加定位不同,压缩感知麦克风阵列声源定位算法可将声源定位转化为稀疏重构问题从而获得较高的性能。但在实际应用环境下,由于远场声源自身指向性、空间混响等原因,声源方向向量往往呈现块稀疏度结构,导致采用传统稀疏恢复算法如正交匹配追踪算法(Orthogonal matching pursuit,OMP)等进行压缩感知定位性能下降。本文在压缩感知声源定位算法中引入块稀疏似零范数,以压缩感知为基本框架,采用块稀疏似零范数稀疏恢复进行声源方向向量的重构,获取声源的方位。实验结果表明,相较于传统声源定位算法和基于OMP的压缩感知声源定位算法,本文算法具有更高的定位精度。

Different from traditional direction of arrival(DOA)estimation algorithms such as steered response power phase transform(SRP-PHAT)algorithm and delay-and-sum(DS)algorithm,the compressed sensing(CS)microphone arrays DOA algorithm transforms the sound source localization into the reconstruction problem of sparse signal to achieve better performance.However,in practical application environment,the direction vector of the far-field sound source tends to exhibit block sparseness due to the sound source directivity,the spatial reverberation and other reasons,which leads to the performance degradation of traditional sparse recovery algorithms such as orthogonal matching pursuit(OMP)algorithm.In this paper,the block approximated l0 is introduced into the microphone array CS DOA algorithm.Under the CS framework,the block approximated l0 sparse recovery is used to reconstruct the direction vector of the sound source to obtain DOA.Experimental results show that the proposed algorithm is capable of yielding higher positioning accuracy compared with traditional algorithms and traditional sparse recovery algorithm using OMP algorithm.