Revolutionizing Underwater Sensor Performance: Tackling Rayleigh Scattering Challenges by Pseudo Random Noise
Abstract: Traditionally, Rayleigh scattering is thought to only impact fiber sensing system performance when the leading fiber is over 10 km long. However, this report illustrates theoretically and experimentally that Rayleigh scattering cannot be ignored in fiber optic interferometric sensor (FOIS) even with several hundred‐meter common leading fiber because of the interaction of Rayleigh backward scattering (RBS) and returning interference signal. Herein, a conceptual framework is developed to elucidate the interaction between RBS and FOIS interference, revealing that, beyond laser monochromacity, the self‐correction characteristic of laser pulses also influences coherent superposition. Building upon this novel insight, a phase modulation method based on pseudorandom noise (PRN) code is first proposed to address coherent RBS stacking on returning FOIS interferences while preserving high laser monochromacity. By modulating the interrogation pulses, a 21.3 dB suppression of background phase noise is achieved in FOIS with 3.3 km leading fiber. This study offers a holistic understanding of Rayleigh scattering in the leading fiber, encompassing experimental observations, theoretical modeling, physics analysis, and its resolution, thereby contributing to advancements in underwater sensing to broaden the understanding of the underwater environment.
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Erschienen in
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Revolutionizing Underwater Sensor Performance: Tackling Rayleigh Scattering Challenges by Pseudo Random Noise ; day:04 ; month:12 ; year:2024 ; extent:13
Advanced science ; (04.12.2024) (gesamt 13)
- Urheber
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Hu, Qihao
Shang, Fan
Ma, Lina
Wang, Wujie
Yu, Yi
Bian, Yujie
Zhu, Xiaoqian
Song, Junqiang
- DOI
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10.1002/advs.202411967
- URN
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urn:nbn:de:101:1-2412091325280.507205126303
- Rechteinformation
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:31 MESZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Hu, Qihao
- Shang, Fan
- Ma, Lina
- Wang, Wujie
- Yu, Yi
- Bian, Yujie
- Zhu, Xiaoqian
- Song, Junqiang
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