机载复杂场景下的低虚警红外目标检测

Low false alarm infrared target detection in airborne complex scenes

机载红外光电探测系统进行下视复杂场景目标探测时,地面虚警干扰源同弱小目标在空间分布上一致,传统算法会导致大量虚警。因此,提出一种基于运动目标特征的多维度特征关联检测算法。该算法首先对复杂场景进行特征点检测,引入基于相对速高比的跳帧机制,对经过图像配准的帧间图像进行差分处理检出候选目标。同时,结合基于核相关滤波的目标相似度方法进行多维多帧关联,进一步抑制虚警并确认目标。实验结果表明,在载机速高比大于30 mrad/s、系统帧时小于10 ms的机载环境下,该算法的平均检测率达到99.13%,虚警率降至10-5。该方法在多种机载复杂场景下得到验证,适合流水并行运算操作,满足工程实践需求。

When an infrared photoelectric detection system detects a target in a complex airborne scene,the spatial distribution of the ground false alarm interference source is consistent with the spatial distribution of the small dim target.Therefore,a multi-dimensional feature association detection algorithm based on moving target features was proposed herein.First,feature points were detected in complex scenes,and a frame skipping mechanism based on the relative velocity-height ratio was introduced.Candidate targets were detected by inter-frame image difference after image registration.Simultaneously,multi-dimension and multi-frame correlations based on the kernel correlation filter were used to suppress false alarms.In an airborne environment where the vehicle speed-to-height ratio is greater than 30 mrad/s and frame time is less than 10 ms,the average detection rate of this algorithm is 99.13%,and the false alarm rate is 10^(−5).This method was verified in various complex scenarios.In addition,it is suitable for pipeline parallel operation and meets the engineering needs.