Short-Chirped-Pulse OFDR Assisted by Negative Quality Factor Analysis of Correlation for Adaptive Distributed Acoustic Sensing

We propose a distributed acoustic sensing technique that utilizes correlation analysis derived from short-chirped-pulse optical frequency-domain reflectometry (OFDR). The performance of the technique is enhanced by negative quality factor (NQF) analysis, which evaluates the reliability of Rayleigh backscattering spectra (RBS) shift readings under vibration. By selectively filtering out valid RBS shift data, we can overcome the intensity response range limitations typically imposed by the sweeping range. Using this approach, we have successfully demonstrated the detection of maximum vibration frequencies up to 1 kHz over a 32 km fiber under test, achieving a signal-to-noise ratio (SNR) of up to 30 dB and a spatial resolution of 14 m. Furthermore, the system's ability to sense vibrations, particularly those of unexpectedly large magnitudes, has been confirmed.