Absolute Distributed Temperature Measurement With μK Noise Level and Fast Response via Raman/Rayleigh Backscattering DTS/DTGS Data Fusion

This letter presents a hybrid approach for distributed temperature measurement, integrating a distributed temperature sensing (DTS) system, based on Raman backscattering, and distributed temperature gradient sensing (DTGS), based on Rayleigh backscattering. The proposed adaptive fusion algorithm integrates the accumulated average of the DTS signals with the fast variations captured by the DTGS, enabling the reconstruction of thermal profiles with enhanced accuracy and capacity for absolute measurements and fast temporal response. The approach was experimentally validated in a controlled thermal environment, demonstrating good agreement with reference sensors and standing out for its stability and sensitivity. The findings suggest that the DTS/DTGS fusion represents a promising solution for applications necessitating distributed thermal measurements with high reliability.