红外技术2018，Vol.40Issue(2)：176-182,7.
基于深度学习的目标抗干扰跟踪算法
Target Anti-Jamming Tracking Algorithm Based on Depth Learning
闵召阳 1赵文杰1
作者信息
- 1. 空军航空大学 航空航天情报系,吉林 长春 130022
- 折叠
摘要
Abstract
Aimed at the interference of similar background in the target tracking algorithm and rotation of the target frame, the detection scheme of a single shot MultiBox detector (SSD) is proposed, which effectively avoids drifting of the tracking box. First, pre-training of the depth learning model is carried out on a specific kind of target to be tracked, and target location and tracking are completed by using the fusion discriminant scale space algorithm, which is designed in this paper. Discriminant scale spatial model is used to locate the target; feature detection is carried out in the candidate region; a kind of motion estimation and elimination system is designed to ensure uniqueness of the target of the candidate region:and finally the precise positioning of the target is established. Experiments show that this method can effectively avoid the tracing of the tracking frame, caused by similar background interference and occlusion, and can robustly track a fast-moving target and changes in the scale and shape.关键词
SSD检测/判别尺度空间/目标跟踪Key words
SSD detection/discriminate the scale space/target tracking分类
信息技术与安全科学引用本文复制引用
闵召阳,赵文杰..基于深度学习的目标抗干扰跟踪算法[J].红外技术,2018,40(2):176-182,7.
