抄録
This paper addresses sound source detection in an outdoor environment using a quadcopter with a microphone array. As the previously reported method has a high computational cost, we proposed a sound source detection algorithm called multiple signal classification based on incremental generalized singular value decomposition (iGSVD-MUSIC) that detects the sound source location and temporal activity at low computational cost. In addition, to relax the estimation error problem of a noise correlation matrix that is used in iGSVD-MUSIC, we proposed correlation matrix scaling (CMS) to achieve soft whitening of noise. As CMS requires a parameter to decide the degree of whitening, we analyzed the optimal value of the parameter by using numerical simulation. The prototype system based on the proposed methods was evaluated with two types of microphone arrays in an outdoor environment. The experimental results showed that the proposed iGSVD-MUSIC-CMS significantly improves sound source detection performance, and the prototype system achieves real-time processing. Moreover, we successfully clarified the behavior of the CMS parameter by using a numerical simulation in which the empirically-obtained optimal value corresponded with the analytical result.*
* This work is an extension of our publication “Takuma Ohata et al.: Improvement in outdoor sound source detection using a quadrotor-embedded microphone array, IROS 2014, pp. 1902-1907, 2014.”
