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 characteristics. 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. © 2013 Tsinghua University Press, and Springer-Verlag.
CITATION STYLE
Tang, J., Gao, X., & Jin, G. (2013). Dim and weak target detection technology based on multi-characteristic fusion. In Lecture Notes in Electrical Engineering (Vol. 187 LNEE, pp. 271–277). https://doi.org/10.1007/978-3-642-33663-8_27
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