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1.Center for Information Photonics & Communications, School of Information Science & Technology, Southwest Jiaotong University, Chengdu 610031 Sichuan, China
2.Department of Automation, Tsinghua University, Beijing 100084, China
3.School of Artificial Intelligence, Shanghai Jiao Tong University, Shanghai 200030, China
4.Department of Electronic Engineering, Tsinghua University, Beijing 100084, China
Lianshan Yan (lsyan@home.swjtu.edu.cn)
Received:12 December 2024,
Revised:17 March 2025,
Accepted:21 March 2025,
Published Online:03 June 2025,
Published:31 August 2025
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Zhou, Y. et al. High-spatiotemporal-resolution distributed Brillouin sensing with transient acoustic wave. Light: Science & Applications, 14, 2198-2212 (2025).
Zhou, Y. et al. High-spatiotemporal-resolution distributed Brillouin sensing with transient acoustic wave. Light: Science & Applications, 14, 2198-2212 (2025). DOI: 10.1038/s41377-025-01848-4.
Real-time wide-area environment sensing is crucial for accessing open-world information streams from nature and human society. As a transformative technique distinct from electrical sensors
distributed optical fiber sensing especially for Brillouin scattering-based paradigm has shown superior bandwidth
power
and sensing range. Still
it suffers from insufficient resolution and timeliness to characterize remote dynamic events. Here we develop TABS—a transient acoustic wave-based Brillouin optical time domain analysis sensor
supporting long-range high-spatiotemporal-resolution distributed sensing. By designing a functionally synergistic sensor architecture
TABS elaborately leverages wideband and time-weighted energy transformation properties of a transient acousto-optic interaction to breaking through Brillouin-energy-utilization-efficiency bottleneck
enabling enhancements in overall sensing performance. In the experiment
TABS has achieved a 37-cm spatial resolution over a 50-km range with 1 to 2 orders of magnitude improvement in temporal resolution compared to prevailing Brillouin sensing approaches. For the first time
TABS is explored for state imaging of evacuated-tube maglev transportation system as an exemplary application
showcasing its feasibility and flexibility for potential open-world applications and large-scale intelligent perception.
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