Adaptive Temporal Matched Filtering for Noise Suppression in Fiber Optic Distributed Acoustic Sensing

Area of Science:

• Optoelectronics
• Signal Processing
• Fiber Optic Sensing

Background:

• Phase-sensitive optical time domain reflectometry (ϕ-OTDR) is crucial for distributed vibration sensing.
• Fading noise in coherent detection-based ϕ-OTDR systems degrades performance.
• Existing methods struggle with high-frequency events and impact system bandwidth.

Purpose of the Study:

• To present a new digital processing technique for reducing fading noise in fiber optic distributed acoustic vibration sensing.
• To improve the signal-to-noise ratio (SNR) without compromising the frequency response.
• To offer a solution effective for high-frequency vibration detection.

Main Methods:

• Temporal adaptive processing of ϕ-OTDR signals.
• Algorithm based on signal-to-noise ratio (SNR) maximization.
• Validation through laboratory experiments and field tests.

Main Results:

• Achieved over 10 dB improvement in SNR values.
• Demonstrated no reduction in system bandwidth.
• Showcased the effectiveness without additional optical hardware.

Conclusions:

• The proposed adaptive processing approach effectively mitigates fading noise in ϕ-OTDR systems.
• This method enhances distributed acoustic vibration sensing performance without bandwidth limitations.
• The technique is suitable for developing advanced fiber optic-based sensing systems.