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首页> 外文会议>2016 IEEE International Workshop on Acoustic Signal Enhancement >Multichannel time delay estimation for acoustic source localization via robust adaptive blind system identification
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Multichannel time delay estimation for acoustic source localization via robust adaptive blind system identification

机译：基于鲁棒自适应盲系统识别的声源定位多通道时延估计

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摘要

In the problem of acoustic source localization, time difference of arrival (TDOA) among multiple sensors is needed, which is often obtained through time delay estimation (TDE) techniques. Among the multiple TDE methods developed in the literature, the normalized multichannel frequency-domain least-mean-square (NMCFLMS) algorithm is shown robust to reverberation. The performance of this algorithm, however, deteriorates in non-Gaussian and low signal-to-noise ratio (SNR) Gaussian noise environments. In this paper, we re-derive a robust normalized multichannel frequency-domain least-mean-M-estimate (RNMCFLMM) algorithm to estimate TDOAs for acoustic source localization. The proposed algorithm exploits the non-sensitivity of an M-estimator to non-Gaussian noise and makes a tradeoff between the least-squares and least-absolute criteria to improve the robustness of TDE with respect to non-Gaussian and Gaussian noises. The effectiveness of the proposed algorithm is demonstrated in real acoustic environments.
机译：在声源定位问题中，需要多个传感器之间的到达时间差（TDOA），这通常是通过时延估计（TDE）技术获得的。在文献中开发的多种TDE方法中，标准化多通道频域最小均方（NMCFLMS）算法显示出对混响的鲁棒性。但是，在非高斯和低信噪比（SNR）高斯噪声环境中，该算法的性能会下降。在本文中，我们重新推导了鲁棒的归一化多通道频域最小均值M估计（RNMCFLMM）算法，以估计用于声源定位的TDOA。所提出的算法利用了M估计器对非高斯噪声的非敏感性，并在最小二乘和最小绝对准则之间进行权衡，以提高TDE对非高斯和高斯噪声的鲁棒性。该算法的有效性在真实的声学环境中得到了证明。

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