针对相位敏感光时域反射计型分布式光纤围栏入侵监测系统对外界干扰敏感、误报率高的问题进行了深入研究，比较了多种小波提取入侵信号突变特征方法，并提出一种基于多个小波分解结果进行综合判决来降低分布式光纤围栏误报率的方法.实验结果表明，多种小波分解可以分别提取不同层次的突变细节信息，为综合决策提供更完备的信息和条件，比单一判决能更有效降低系统误报率，室外长期测试可达到01次/24h，大大提高了分布式光纤围栏报警系统的稳定性和置信度水平.

Because the distributed fiber fence system based on the phasesensitive optical timedomain reflectometer is very sensitive to its ambient environments, high false alarm rate is a quite normal phenomenon which is very annoying and difficult to avoid. In this paper, different wavelet decomposition methods are compared for extracting the singularity information buried in the noisy intrusion signals. A comprehensive judgment method is proposed which combines several different wavelet decomposition methods to reduce the system′s false alarm rate. The experiment results show that different wavelet decomposition methods can extract different detail information at different levels, thus it can provide much more sufficient information and conditions for the decisionmaking process. The false alarm rate of the new method can be lowered to none or once per 24 hours, which is much lower than the other methods based on a single wavelet analysis way. It can efficiently improve the system′s robustness and its decision′s confidence level.