Tuna Cagdas, Jones Douglas L, Zhao Shengkui, Nguyen Thi Ngoc Tho
Advanced Digital Sciences Center (ADSC), Illinois at Singapore Private Limited, 1 Create Way, #14-02, Create Tower, Singapore 138602, Singapore.
J Acoust Soc Am. 2018 Jun;143(6):3899. doi: 10.1121/1.5042214.
Noise-mapping is an effective sound visualization tool for the identification of urban noise hotspots, which is crucial to taking targeted measures to tackle environmental noise pollution. This paper develops a high-resolution wideband acoustic source mapping methodology using a portable microphone array, where the joint localization and power spectrum estimation of individual sources sparsely distributed over a large region are achieved by tomographic imaging with the multi-frequency delay-and-sum beamforming power outputs from multiple array positions. Exploiting the fact that a wideband source has a common spatial signal-support across the frequency spectrum, two-dimensional tomographic maps are produced by applying compressive sensing techniques including group least absolute shrinkage selection operator formulation and sparse Bayesian learning to promote group sparsity over multiple frequency bands. The high-resolution mapping is demonstrated with experimental data recorded with a microphone array mounted atop an electric vehicle driven along a road while playing audio clips from a loudspeaker positioned within the adjacent open field.
噪声映射是一种用于识别城市噪声热点的有效声音可视化工具，这对于采取针对性措施应对环境噪声污染至关重要。本文开发了一种使用便携式麦克风阵列的高分辨率宽带声源映射方法，通过对多个阵列位置的多频延迟求和波束形成功率输出进行层析成像，实现了在大区域内稀疏分布的单个声源的联合定位和功率谱估计。利用宽带声源在整个频谱上具有共同空间信号支持这一事实，通过应用包括组最小绝对收缩选择算子公式和稀疏贝叶斯学习在内的压缩感知技术来促进多个频带上的组稀疏性，从而生成二维层析图。通过安装在沿道路行驶的电动汽车顶部的麦克风阵列记录的实验数据进行了高分辨率映射演示，同时从位于相邻开阔场地内的扬声器播放音频片段。
