一种有效降低红外预警系统虚警率的检测算法

An Efficient Detection Algorithm for Decreasing False Alarm Rate of Infrared Surveillance System

为了解决红外预警系统在受到地物、云层、飞鸟等干扰点的影响下,目标探测虚警率高的问题,提出一种基于目标点角坐标变化的检测算法。该算法是先通过分析系统扫描到的目标点角速度变化情况,将可能的目标点从含有噪声的背景中分离出来;然后利用内点惩罚函数及最速下降法相结合的最优值算法求出每个目标点的航路;最后,对航路的真实性进行判断,从而检测出运动目标。通过实验证明了该算法抗噪声干扰能力强,易于硬件实现,能够有效地降低红外预警系统的虚警率。

Because of the influence of surface objects, such as clouds and birds, etc., the false alarm rate of infrared surveillance system is easy to be higher than the imagined. In order to decrease its false alarm rate effectively, a detection algorithm is researched by analyzing the changes of object’s angle coordinate. An optimal method is used which combines the interior point penalty function method and the steepest descent algorithm, so as to judge the routes of all the correlative objects and to differentiate the real object from all the interferences. At last, some experiments were carried out to prove that the proposed method can improve the anti-interference capability and decrease the false alarm rate in real time.