In the past three decades, Brillouin optical time domain reflectometry (BOTDR) has attracted widespread attention from researchers and has been applied to health and safety monitoring in various engineering structures. BOTDR based on short-time Fourier transform (STFT) performs signal processing on the broadband signal of the Brillouin scattering spectrum. The acquisition time of the broadband signal is shorter than that of the frequency sweep system, and therefore system response is swifter. Spatial resolution and frequency resolution are two important performance parameters of the STFT-BOTDR system. The former, spatial resolution, is proportional to optical pulse width and related to the form and length of the window function. The latter is related to the signal-to-noise ratio of the electrical signal, step length of frequency, center frequency of the Brillouin gain spectrum, and full width at half maximum. The two resolutions correlate with each other. Meanwhile, the computing time of the STFT is related to the set parameters of frequency step length and of the sliding window. As a result, improving the system frequency resolution will increase the system's computing time. How can we optimize the photoelectric design and improve the efficiency of the demodulation algorithm under the current system of typical BOTDR to obtain highly enhanced spatial resolution by using economic optical pulses of common width (instead of using narrow pulses and other costly photoelectric modules)? The solution to the question is essential to the extensive and large-scale application of BOTDR in the engineering field.

We propose a maximum-seeking method based on the BOTDR system, which realizes the rapid positioning of frequency shift and the enhancement of system spatial resolution based on fast Fourier transform (FFT) and STFT. The maximum-seeking method based on the equal division FFT process first performs FFT processing on the time-domain signal and linear fitting and then maximum-seeking processing on the spectrum within the frequency range of 100 MHz on both sides of the Brillouin center frequency. Then, by using the judgment Eq. (5), it determines whether there is temperature variation or strain information and then continuously divides the time-domain signal. Finally, it selects the corresponding length of the time-domain signal to determine the temperature variation or strain frequency shift range, thus realizing the rapid positioning of frequency shift and reducing the system's operation time. The maximum-seeking method based on STFT first processes the time-domain signal with STFT to construct a three-dimensional Brillouin gain spectrum and then builds a Brillouin frequency shift distribution through the maximum-seeking method. The Brillouin frequency shift curve is corrected by using the judgment Eq. (7) in different situations, determining the length of the short-distance temperature variation or strain segment, thereby improving the system's spatial resolution.

In the experiment, we design a BOTDR system based on STFT and quickly locate the heated fiber in a section of 130 m the fiber of 2 km under test. We use the spectrum constructed with equal division FFT (Fig. 6) to determine the position of temperature occurrence based on whether the frequency shift peaks appear in each segment of the spectrum. The traditional STFT-BOTDR system detects fiber temperature variation data of 130 m in 12800 groups of data, with a system operation time of 482 s. By using the maximum-seeking method based on equal division FFT, the system operation time for detecting the temperature variation information of 130 m is reduced to 68 s, which is 1/8 of the original time. The calculation speed is much improved. At the same time, to verify the enhancement of spatial resolution by using the maximum-seeking method based on STFT, we design test fiber 2 (Fig. 7) with heating section temperatures set at 40 °C and 50 ℃. Under the condition of setting the probe light pulse width to 100 ns, we use the traditional peak search algorithm and the maximum-seeking method to process the constructed Brillouin frequency shift distribution (Fig. 9). From the experimental data of Brillouin frequency shift distribution (Fig. 9), it can be seen that after using the STFT-based maximum-seeking method, the system's spatial resolution is optimized from 12.8 m to 1.2 m under the heating section at 40 °C and from 4.6 m to 0.6 m under the heating section at 50 ℃.

We propose a new method to achieve rapid frequency shift positioning and spatial resolution enhancement in the BOTDR by using the maximum-seeking method. By continuously dividing the original signal and performing FFT processing, the maximum-seeking method processes the two-dimensional Brillouin gain spectrum to determine the position range of temperature variation or strain segments, reducing the system's computing time. At the same time, the three-dimensional Brillouin gain spectrum obtained from STFT is processed by using the maximum-seeking method to construct Brillouin frequency shift distribution, reducing the minimum detectable temperature variation or strain segment length and enhancing the system's spatial resolution. In the experiment, an STFT-based BOTDR system is designed. By using the maximum-seeking method based on equal division FFT, the heated fiber of 130 m in the test fiber of 2 km is quickly located, reducing the system's operation time to 1/8 of the original and improving calculation speed. Simultaneously, under the condition of setting the probe light pulse width to 100 ns, a spatial resolution of 0.6 m is achieved on the test fiber of 2 km. The experimental results show that this method can further improve the performance of existing STFT-BOTDR systems without sacrificing other sensing performance parameters. By using the maximum-seeking method based on STFT, the sub-meter level spatial resolution is achieved. Compared with the traditional BOTDR system, the STFT-BOTDR system based on the maximum-seeking method has faster detection speed and better spatial resolution in engineering applications. Besides, this method helps to obtain higher system performance under limited system cost, making it easier for low-cost and high-precision BOTDR systems to be used in larger quantities at construction sites, bridges, and other occasions, thereby accelerating the engineering and large-scale application of distributed fiber optic sensing technology.