Fast Brillouin optical time-domain analysis using frequency-agile and compressed sensing

Area of Science:

• Optical sensing
• Signal processing
• Photonics

Background:

• Brillouin optical time-domain analysis (BOTDA) is a key technique for distributed strain and temperature sensing.
• Conventional BOTDA methods can be limited by sampling rates and data storage requirements.
• Developing faster and more efficient BOTDA systems is crucial for real-time monitoring applications.

Purpose of the Study:

• To propose and experimentally demonstrate a fast BOTDA sensor using frequency-agile and compressed-sensing techniques.
• To enhance the sampling rate and reduce data storage in BOTDA systems.
• To improve the overall sensing performance of BOTDA.

Main Methods:

• Employed a frequency-agile and compressed-sensing technique for BOTDA.
• Utilized a data-adaptive sparse base obtained by principal component analysis for Brillouin spectrum representation.
• Applied random frequency sampling and orthogonal matching-pursuit algorithms for spectrum reconstruction.
• Mapped the Brillouin gain spectrum (BGS) with a frequency step of 4 MHz and span of 500 MHz.

Main Results:

• Successfully recovered the BGS using only 37 random frequency samples, representing 30% of the full data.
• Achieved a 3.3-time increase in the sampling rate compared to conventional fast BOTDA.
• Reduced data storage requirements by 70% through compressed-sensing technology.
• Demonstrated improved sensing performance with fewer sampling frequencies.

Conclusions:

• The proposed compressed-sensing technique significantly enhances the speed and efficiency of BOTDA sensors.
• This method enables faster data acquisition and reduced data storage, making BOTDA more practical for demanding applications.
• The frequency-agile and compressed-sensing approach offers a promising pathway for next-generation optical sensing systems.