基于高阶矩阵函数的广义逆波束形成改进算法

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摘要广义逆波束形成是一种高效的声源识别定位方法，然而其计算稳健性易受随机噪声影响，阻碍了其声源识别动力学水平进一步提高。为改善广义逆波束形成声源识别方法的稳健性，基于高阶矩阵函数提出一种广义逆波束形成改进算法：定义了基于广义逆波束形成的正则化矩阵；对正则化矩阵与波束形成输出进行迭代运算；利用高阶矩阵函数对迭代求解所得广义逆波束形成输出的互谱进行优化。通过数值仿真详细分析了声源频率对波束形成矩阵函数阶次取值的影响，得到阶次的最优取值区间。最后通过数值模型和实验算例对单极子与相干声源进行定位识别，结果表明:改进算法在准确识别声源基础上能有效抑制旁瓣干扰，且具有更高的声源识别精度。

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关键词 ：传声器阵列, 声源识别, 广义逆波束形成, 高阶矩阵函数

Abstract：

Generalized inverse beamforming is an effective sound source locating method. But its calculation robustness is sensitive to random noises. For the sake of improving the robustness of generalized inverse beamforming, a modified algorithm based on high-order matrix function is proposed. The regularization matrix is defined based on generalized inverse beamforming and used in iteratively resolving beamforming output. At the same time, the high-order matrix function is incorporated into the cross spectra of beamforming output to optimize the effect of sound source localization. Moreover, to find the optimum range of matrix function order, the numerical simulation is implemented and the influence of sound source frequency on value selection of matrix function order is analyzed correspondingly. Finally, the identifications of both monopole and coherent sound sources are realized numerically and experimentally. The results show that the proposed modified algorithm can identify the source position with higher space resolution and less side-lobe.

Key words： microphones array sound source identification generalized inverse beamforming high order matrix function

收稿日期: 2015-07-28 出版日期: 2017-05-15

引用本文:

陈思 2，张志飞 1，2，徐中明 1，2，贺岩松 1，2，黎术 2. 基于高阶矩阵函数的广义逆波束形成改进算法[J]. 振动与冲击, 2017, 36(10): 98-103.
Chen Si 1 Zhang Zhi-fei 1 Xu Zhong-ming 1 He Yan-song 1 Li Shu 1 . Modified Generalized Inverse Beamforming Based on High-order Matrix Function. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(10): 98-103.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2017/V36/I10/98

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