基于辐射累积和空间反演的空中弱目标检测算法

背景辐射噪声是弱信号检测面临的难点问题。提出了一种显著提升信噪比实现匀速运动弱目标的有效检测算法。建立目标坐标空间和速度空间,以不同速度矢量控制图像叠加,形成提升了信噪比的新的图像序列并构成图像空间;利用恒虚警判决法在图像空间中检测候选目标点;根据候选目标点所对应的坐标向量和速度向量分别映射到坐标空间和速度空间,由两个空间中出现的峰值判定目标点。实际红外成像系统实拍实验表明,算法能将信噪比提升至接近原图的N倍,目标检测概率和虚警概率都明显优于所对比的弱目标检测算法。

Dim air target detection based on radiation accumulation and space inversion

Background radiation noise interference is a difficult technical problem for dim signal detection. A dim target detection algorithm was proposed which can significantly improve signal-to-noise ratio(SNR) to achieve uniformly motion dim target detection successfully. Firstly, a coordinate space and a velocity space were established. Then the original image sequence was stacked along different velocity vectors to acquire a new image sequence with SNR improved and the new image sequence forms an image space. Secondly, quasi-target points in the image space were detected by constant false-alarm ratio(CFAR) judging. Finally, velocity vectors and coordinate vectors of quasi-target points were mapped to the velocity space and the coordinate space respectively. As a result, two local peaks from the spaces will confirm true target points.Experiments of real images from actual IR imaging system show that proposed algorithm can improve SNR approximately up to N times of original image SNR, and the proposed algorithm is demonstrably superior to compared algorithms on detection probability and false alarm probability.