In response to the technical issue in Raman distributed optical fiber technology where the traditional meter-level spatial resolution performance is insufficient, leading to a decline in system measurement accuracy within sub-spatial resolution fiber segments along the sensing fiber, a threshold coefficient fitting technique based on a one-dimensional peak-seeking method is proposed in this study. Significant temperature measurement errors of up to tens of degrees Celsius are caused by the overlap of Raman scattering signals from non-detection regions when the detection fiber length is shorter than the system's spatial resolution. This severely limits the technology application in scenarios requiring precise temperature monitoring. To overcome the above bottleneck, a purely algorithmic approach is introduced, which reconstructs the temperature field without requiring hardware modifications. The sensing fiber was globally scanned using the one-dimensional peak-finding algorithm to precisely locate sub-spatial resolution detection fiber regions. Simultaneously, the peak intensity, full width at half maximum (FWHM), and location were extracted from the temperature rise curve within the fiber under test (FUT). Through pre-calibration experiments, a quantitative fitting model was established between peak temperature rise curves and threshold coefficients, revealing a quantitative mapping relationship between FWHM and sensing distance, as well as length of FUT. The results indicated that FWHM exhibited a significant positive linear correlation with sensing distance, independent of temperature variations. This characteristic enabled FWHM to serve as a reliable feature parameter for identifying the actual length of detection fibres. During real-time measurements, the detection fiber length was determined via the mapping model based on extracted FWHM and location. Then the corresponding threshold coefficient fitting model is selected to compensate for distorted temperature rise peaks, thereby reconstructing distributed temperature field. Experimental results demonstrated that over a 10-kilometre sensing distance, the results indicate that the application of this technique significantly enhanced the temperature measurement accuracy within the 30 cm detection fiber, achieving 1.5 °C compared to the baseline accuracy of 34.7 °C before compensation. Conclusions indicate that the proposed threshold coefficient fitting technique, through algorithmic innovation, effectively overcomes the technical limitation of deteriorating temperature measurement accuracy in sub-spatial resolution regions within Raman distributed fibre optics sensing. The constructed FWHM quantitative mapping model provides critical basis for threshold compensation, ultimately achieving precise temperature monitoring of sub-metre regions within long-distance sensing contexts. This solution features a streamlined structure, low cost, and ease of engineering integration. It offers a novel approach for long-term, high-precision temperature monitoring in fields such as power cable fault orienation, oil and gas pipeline micro-leakage early warning, and civil structural health monitoring.
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