现有的异常轨迹检测算法往往侧重于检测轨迹的空域异常, 忽略了对轨迹时域异常的检测, 并且检测精确度不高, 针对此类问题, 提出了基于增强聚类的异常轨迹检测算法。首先, 采用基于速度的最小描述长度(VMDL)准则把轨迹简化成有序线段; 然后, 使用改进的线段间的距离定义, 基于DBSCAN算法把线段分为不同的类, 以建模局部正常运动模式; 最后, 采用先检测空间异常性再检测时间异常性的二级检测算法, 检测时空异常轨迹点。在多个测试集上的实验结果表明: 该算法可以检测位置、角度、速度等三种时空异常轨迹点, 相对于其他算法, 明显提高了异常轨迹检测的精确度。

Optical fiber vibration is detected by the coherent optical time domain reflection technique. In addition to the vibration signals, the reflected signals include clutters and noises, which lead to a high false alarm rate. The “cell averaging” constant false alarm rate algorithm has a high computing speed, but its detection performance will be declined in nonhomogeneous environments such as multiple targets. The “order statistics” constant false alarm rate algorithm has a distinct advantage in multiple target environments, but it has a lower computing speed. An intelligent two-level detection algorithm is presented based on “cell averaging” constant false alarm rate and “order statistics” constant false alarm rate which work in serial way, and the detection speed of “cell averaging” constant false alarm rate and performance of “order statistics” constant false alarm rate are conserved, respectively. Through the adaptive selection, the “cell averaging” is applied in homogeneous environments, and the two-level detection algorithm is employed in nonhomogeneous environments. Our Monte Carlo simulation results demonstrate that considering different signal noise ratios, the proposed algorithm gives better detection probability than that of “order statistics”.

在光纤振动信号检测系统中，使用相位敏感光时域反射技术，可检测长距离的光纤振动信号，但反射回的光信号都有大量的振动杂波和噪声，导致振动检测信号的虚警率较高。提出采用单元平均恒虚警(CA-CFAR)和有序统计恒虚警(OS-CFAR)二级检测算法，保持虚警率稳定，既提高了运算速度，也改善了参考单元中存在多个目标的检测性能，并提出利用蒙特卡罗方法确定二级检测的门限系数，最后通过蒙特卡罗仿真及现场实验验证，对算法进行了性能分析，验证了算法的可行性以及有效性。