Dim and Weak Target Detection Technology Based on Multi-Characteristic Fusion

摘要

As the signal of small weak target is weak,its characteristic information is prone to weakening and loss and is difficult to maintain stability.In this paper,a self-learning mechanism is built using continuous signal correlative characteris-tics.The method is based on K-L transform fusion technology and D-S theory of decision-making.Meanwhile,the fusion technology of "fusion after the first decision-making" and "decision-making after first fusion" organic integration is developed.To verify the detection capability of this technology for small dim targets,a new type of tracking processor is developed.It processes more than one hundred groups of raw image data divided into two groups.The image data is taken by a space target surveillance telescope.Experimental results show that dim targets can be detected and tracked stably and reliably using this technology.Also provided with a complex background suppression and anti-jamming capability,a target can be detected stably and reliably when its SNR is about 1.2.