分布式光纤中的稳健时间延迟估计方法

 在分布式光纤传感系统定位中，传统时延估计算法常由于噪声相关性较强而失效。采用一种削弱相关噪声的改进型广义相关法，并针对系统特点，为进一步改善分布式光纤传感定位的准确度与稳定度，提出了一种先对数据按事件信号进行分帧，再采用卡尔曼滤波器对分帧时延估计结果进行跟踪的时延估计方案。系统仿真实验与实际数据测试结果均表明：提出的时延估计方案能够有效抑制强相关性的噪声，提高时延估计的准确度与稳定度。经大量现场测试，本文的方案能够有效地将时延估计误差稳定地控制在0.2个采样间隔以内，能够满足系统实际定位精度要求。

Robust time delay estimation of distributed optical fiber sensor system

In the positioning problem of distributed optical fiber sensor system, traditional time delay estimation (TDE) algorithms usually fail due to strongly correlated noise.A modified general cross correlation method was used to remove the correlated noise. According to the system features, a new TDE scheme was proposed to further improve the distributed optical fiber sensor system performance on accuracy and stability. The received data were first divided into many frames on the basis of "event signal" and then Kalman filter was applied to track the TDE results of the data frames. Simulation experiments and real data tests indicated that the proposed TDE scheme had good performance to suppress the correlated noise and improve the TDE accuracy and stability. Lots of on-site tests proved the TDE error was stably controlled below the sampling interval of 0.2, which satisfied the system accuracy requirement.