Gerstoft Peter, Mecklenbräuker Christoph F, Seong Woojae, Bianco Michael
Noise Lab, University of California San Diego, La Jolla, California 92093-0238, USA.
Institute of Telecommunications, Vienna University of Technology, 1040 Vienna, Austria.
J Acoust Soc Am. 2018 Jun;143(6):3731. doi: 10.1121/1.5043089.
Compressive sensing (CS) in acoustics has received significant attention in the last decade, and thus motivates this special issue. CS emerged from the signal processing and applied math community and has since generated compelling results in acoustics. This special issue primarily addresses the acoustics CS topics of compressive beamforming and holography. For a sound field observed on a sensor array, CS reconstructs the direction of arrival of multiple sources using a sparsity constraint. Similarly, in holography a sparsity constraint gives improved sound field reconstruction over conventional ℓ-regularization. Other topics in this issue include sparse array configurations (as co-arrays) and sparse sensing in acoustic communication.
在过去十年中，声学中的压缩感知（CS）受到了广泛关注，因此促成了本期特刊。压缩感知起源于信号处理和应用数学领域，此后在声学领域取得了令人瞩目的成果。本期特刊主要探讨压缩波束形成和全息术等声学压缩感知主题。对于在传感器阵列上观测到的声场，压缩感知利用稀疏性约束来重建多个声源的到达方向。类似地，在全息术中，与传统的ℓ正则化相比，稀疏性约束能实现更好的声场重建。本期特刊的其他主题还包括稀疏阵列配置（作为协同阵列）以及声学通信中的稀疏传感。
