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一种受海豚启发的用于水下声学成像的紧凑型声纳。

A dolphin-inspired compact sonar for underwater acoustic imaging.

作者信息

Vishnu Hari, Hoffmann-Kuhnt Matthias, Chitre Mandar, Ho Abel, Matrai Eszter

机构信息

Acoustic Research Laboratory, Tropical Marine Science Institute, National University of Singapore, 18 Kent Ridge Road, Singapore, 119227, Singapore.

Ocean Park Hong Kong, 180 Wong Chuk Hang Road, Aberdeen, Hong Kong SAR, China.

出版信息

Commun Eng. 2022 Jun 8;1(1):10. doi: 10.1038/s44172-022-00010-x.

Abstract

Underwater imaging sonars are widely used for oceanic exploration but are bulky and expensive for some applications. The sonar system of dolphins, which uses sound pulses called clicks to investigate their environment, offers superior shape discrimination capability compared to human-derived imaging sonars of similar size and frequency. In order to gain better understanding of dolphin sonar imaging, we train a dolphin to acoustically interrogate certain objects and match them visually. We record the echoes the dolphin receives and are able to extract object shape information from these recordings. We find that infusing prior information into the processing, specifically the sparsity of the shapes, yields a clearer interpretation of the echoes than conventional signal processing. We subsequently develop a biomimetic sonar system that combines sparsity-aware signal processing with high-frequency broadband click signals similar to that of dolphins, emitted by an array of transmitters. Our findings offer insights and tools towards compact higher resolution sonar imaging technologies.

摘要

水下成像声纳广泛应用于海洋探索,但对于某些应用来说体积庞大且价格昂贵。海豚的声纳系统利用称为滴答声的声脉冲来探测周围环境,与类似尺寸和频率的人造成像声纳相比,具有卓越的形状辨别能力。为了更好地理解海豚声纳成像,我们训练一只海豚通过声学方式询问某些物体并进行视觉匹配。我们记录海豚接收到的回声,并能够从这些记录中提取物体形状信息。我们发现,将先验信息,特别是形状的稀疏性,融入到处理过程中,能比传统信号处理更清晰地解释回声。随后,我们开发了一种仿生声纳系统,该系统将稀疏感知信号处理与由一系列发射器发出的类似于海豚的高频宽带滴答声信号相结合。我们的研究结果为紧凑型高分辨率声纳成像技术提供了见解和工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf5b/11341816/92274c66c6b1/44172_2022_10_Fig1_HTML.jpg

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