journal article·2025-01Open access

Revolutionizing Underwater Sensor Performance: Tackling Rayleigh Scattering Challenges by Pseudo Random Noise

Qihao Hu, Fan Shang, Lina Ma, Wujie Wang, Yi Yu, Yujie Bian, Xiaoqian Zhu, Junqiang Song

Advanced Science· Volume 12· Issue 4

Abstract

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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Advanced Fiber Optic Sensors · Advanced Fiber Laser Technologies · Seismic Waves and Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Meteorology and Oceanography National University of Defense Technology Changsha Hunan 410073 China

Funding

National Natural Science Foundation of China

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