【摘要】 基于到达时间差(Time difference of arrival,TDOA)估计的方法是声源波达方向(Direction of arrival,DOA)估计中的一类重要方法。其中由TDOA到DOA的映射是该类方法的关键步骤。本文提出了一种基于多核聚类最小二乘支持向量回归(Least-squares support vector regression,LS-SVR)的TDOA-DOA映射方法,并且分析了其稀疏化处理后的性能。为了提高混响噪声环境下的TDOA-DOA映射性能,本文还给出了一种基于归一化中值滤波的TDOA估计离群值消除方法。仿真结果表明,本文提出的方法要优于现有的最小二乘方法以及单核LS-SVR方法。更多还原

【Abstract】 In sound source direction of arrival(DOA)estimation,one of the typical methods is based on the time difference of arrival(TDOA).For the TDOA-based sound source DOA estimation,the TDOADOA mapping is a crucial step.Here,we propose a TDOA-DOA mapping approach based on the multikernel least-squares support vector regression(LS-SVR),and also analyze its performance with sparsification.In addition,we present an outlier detection method based on the normalized median filtering to post-process the TDOA estimation for improving the performance of TDOA-DOA mapping in noisy reverberant environments.Simulation results show that the proposed method is superior to its counterparts,such as LS and single-kernel LS-SVR methods.更多还原