基于相关编码的光纤拉曼温度传感系统的解码算法研究

Research on decoding algorithm of correlation coding for fiber Raman distributed temperature sensor system

针对相关编码技术中传统解码运算的计算效率低和存储空间大的问题,利用重叠保留法对拉曼散射信号进行分段处理,并采用基于快速傅立叶变换(FFT)的循环相关代替各个分段内的离散线性相关,最后将各段结果组合完成对系统的解码运算。在512bit Golay编码的20km光纤拉曼温度传感仿真系统中,解码时间由传统移位相关算法的0.228s减少到了0.025s,提高了8倍以上的解码效率,解码过程中FFT运算所需的存储空间由传统循环相关算法的1 280 000bit减少到了65 536bit,减小了19倍以上的存储空间。上述结果表明,本文方法是一种实时有效的解码方法。

Correlation coding technology can effectively improve the signabto-noise ratio of a fiber Raman distributed temperature sensor system. However, the traditional decoding algorithm in this technique needs a lot of calculation and memory space. To solve the two problems, a method of overlap saving is proposed to cut Raman scattering signals into segments. Furthermore, the traditional discrete linear cor- relation decoding algorithm is replaced by the circular correlation decoding algorithm which is based on the fast Fourier transform （FFT） in each segment. Finally,the results of each segment are combined to- gether to complete the decoding of the system. In the simulation of a 20 km fiber Raman distributed tem- perature sensor system which is based on 512 bit Golay pulse coding sequence, the time of the circular correlation decoding process can be reduced by more than eight times from 0. 228 s to 0. 025 s compared with the traditional discrete linear correlation decoding process. In the mean time, the memory space of the FFT module can be reduced by more than 19 times from 1 280 000 bit to 65 536 bit compared with the traditional discrete linear correlation decoding process. The above results indicate that the decoding method is efficient and can be performed in real time.