Noise correlation matrix estimation for improving sound source localization by multirotor UAV

Koutarou Furukawa, Keita Okutani, Kohei Nagira, Takuma Otsuka, Katsutoshi Itoyama, Kazuhiro Nakadai, Hiroshi G. Okuno

研究成果: Conference contribution

54 被引用数 (Scopus)

抄録

A method has been developed for improving sound source localization (SSL) using a microphone array from an unmanned aerial vehicle with multiple rotors, a 'multirotor UAV'. One of the main problems in SSL from a multirotor UAV is that the ego noise of the rotors on the UAV interferes with the audio observation and degrades the SSL performance. We employ a generalized eigenvalue decomposition-based multiple signal classification (GEVD-MUSIC) algorithm to reduce the effect of ego noise. While GEVD-MUSIC algorithm requires a noise correlation matrix corresponding to the auto-correlation of the multichannel observation of the rotor noise, the noise correlation is nonstationary due to the aerodynamic control of the UAV. Therefore, we need an adaptive estimation method of the noise correlation matrix for a robust SSL using GEVD-MUSIC algorithm. Our method uses a Gaussian process regression to estimate the noise correlation matrix in each time period from the measurements of self-monitoring sensors attached to the UAV such as the pitch-roll-yaw tilt angles, xyz speeds, and motor control values. Experiments compare our method with existing SSL methods in terms of precision and recall rates of SSL. The results demonstrate that our method outperforms existing methods, especially under high signal-to-noise-ratio conditions.

本文言語English
ホスト出版物のタイトルIEEE International Conference on Intelligent Robots and Systems
ページ3943-3948
ページ数6
DOI
出版ステータスPublished - 2013
外部発表はい
イベント2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo
継続期間: 2013 11 32013 11 8

Other

Other2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013
CityTokyo
Period13/11/313/11/8

ASJC Scopus subject areas

  • 制御およびシステム工学
  • ソフトウェア
  • コンピュータ ビジョンおよびパターン認識
  • コンピュータ サイエンスの応用

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