基于分类的感兴趣目标检测算法及仿真验证  

Classification-based interested target detection algorithm and simulation verification

作　　者：王立鹏 刘宾[1,2] 闫文敏 项祎祎 张新玉 WANG Li-peng;LIU Bin;YAN Wen-min;XIANG Yi-yi;ZHANG Xin-yu(College of Information and Communication Engineering,North University of China,Taiyuan 030051,China;Shanxi Key Laboratory of Signal Capturing and Processing,North University of China,Taiyuan 030051,China;Science and Technology on Transient Impact Laboratory,Beijing 102202,China)

机构地区：[1]中北大学信息与通信工程学院,山西太原030051 [2]中北大学信息探测与处理山西省重点实验室,山西太原030051 [3]瞬态冲击技术重点实验室,北京102202

出　　处：《传感器与微系统》2019年第3期141-143,146,共4页Transducer and Microsystem Technologies

摘　　要：针对在弹丸冲击靶板后效过程中,由于靶板破片对弹丸的遮挡,影响对弹丸姿态等信息的获取的问题,提出了一种群目标分类的合成孔径成像算法,利用分类结果筛选多视角图像中感兴趣目标,以某一视角为参考进行合成孔径成像,减少前景遮挡对目标信息探测的干扰。仿真实验结果表明:该算法能够有效去除弹丸前景的遮挡物,提高了弹丸目标的重建质量,验证了所提算法的有效性。During the aftereffect of the bullet impacting target plate,due to the occlusion of the bullet by fragments of the target plate,acquisition of information such as how the bullet posture is affected.Aiming at this problem,a synthetic aperture imaging algorithm for group target classification is proposed.The classification results are used to filter the interested target in multi-view images,and synthetic aperture imaging is performed with reference to a certain angle of view to reduce the interference of foreground occlusion on target information detection.The simulation results show that the occlusion in front of the bullet can be effectively removed and the reconstruction quality of the bullet target is improved sufficiently,which verify the effectiveness of the proposed algorithm.

关 键 词：孔径编码 自适应窗 非目标光线标记 合成孔径成像 

分 类 号：O438[机械工程—光学工程]