麦克风阵列
声源定位
计算机科学
噪音(视频)
多转子
互相关
话筒
协方差矩阵
语音识别
音频信号
信号(编程语言)
算法
人工智能
声音(地理)
声学
工程类
数学
语音编码
电信
物理
声压
数学分析
航空航天工程
图像(数学)
程序设计语言
作者
Sheng Guan,Ruo Jia,Libo Qiao,Guohui Gu,Jianhong Kang,Yujia Song
标识
DOI:10.1007/978-981-99-2653-4_1
摘要
The application of an unmanned aerial vehicle (UAV) equipped with microphone array for field search and rescue has demonstrated good potentials. One of the main issues in using a multirotor UAV for sound source localization is that the ego noise of the UAV’s rotors interferes with the audio observation and degrades the sound source localization performance. This paper introduces a variant of the Multiple signal classification (MUSIC) technique to audio processing embedded in the UAV scenarios, suppressing background noise by employing the noise datasets to reconstruct the covariance matrix. As simulation results are described, the performance improvement is achieved while using the new approach compared with the generalized cross-correlation with phase transform (GCC-PHAT), non-linear generalized cross-correlation (GCC-NONLIN) and conventional MUSIC method.
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