Yin Zhou, Yuan Cheng, Jia Ye, Zonglei Li, Haijun He, Wei Pan, Bin Luo, Lianshan Yan
{"title":"基于瞬态声波的高时空分辨率分布式布里渊传感","authors":"Yin Zhou, Yuan Cheng, Jia Ye, Zonglei Li, Haijun He, Wei Pan, Bin Luo, Lianshan Yan","doi":"10.1038/s41377-025-01848-4","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":18069,"journal":{"name":"Light-Science & Applications","volume":"26 1","pages":""},"PeriodicalIF":20.6000,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"High-spatiotemporal-resolution distributed Brillouin sensing with transient acoustic wave\",\"authors\":\"Yin Zhou, Yuan Cheng, Jia Ye, Zonglei Li, Haijun He, Wei Pan, Bin Luo, Lianshan Yan\",\"doi\":\"10.1038/s41377-025-01848-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":18069,\"journal\":{\"name\":\"Light-Science & Applications\",\"volume\":\"26 1\",\"pages\":\"\"},\"PeriodicalIF\":20.6000,\"publicationDate\":\"2025-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Light-Science & Applications\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.1038/s41377-025-01848-4\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"OPTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Light-Science & Applications","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1038/s41377-025-01848-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"OPTICS","Score":null,"Total":0}
High-spatiotemporal-resolution distributed Brillouin sensing with transient acoustic wave
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.