本文针对复杂背景下红外小目标检测跟踪问题,提出了一种背景自适应的目标检测跟踪方案。针对地面背景下的红外目标检测,采用帧差法,分别提出了跳帧多帧差法和双阈值多帧差法以应对目标长时间静止和灰度对比度下降的问题。针对天空背景...本文针对复杂背景下红外小目标检测跟踪问题,提出了一种背景自适应的目标检测跟踪方案。针对地面背景下的红外目标检测,采用帧差法,分别提出了跳帧多帧差法和双阈值多帧差法以应对目标长时间静止和灰度对比度下降的问题。针对天空背景下的红外目标检测,采用基于目标区域稳定性和显著性(Regional Stability and Saliency, RSS)的检测算法。在检测得到目标备选点后,使用带标签的高斯混合概率假设密度(Gaussian Mixture Probability Hypothesis Density, GMPHD)滤波器对备选点滤波以输出目标初始轨迹。同时引入轨迹整理将间断的初始轨迹重新连接并进一步去除虚警。经过验证,本文提出的目标检测方法可在复杂多类背景下准确检测并跟踪红外图像中的小目标。展开更多
Cross-eye jamming is an electronic attack technique that induces an angular error in the monopulse radar by artificially creating a false target and deceiving the radar into detecting and tracking it.Presently,there i...Cross-eye jamming is an electronic attack technique that induces an angular error in the monopulse radar by artificially creating a false target and deceiving the radar into detecting and tracking it.Presently,there is no effective anti-jamming method to counteract cross-eye jamming.In our study,through detailed analysis of the jamming mechanism,a multi-target model for a cross-eye jamming scenario is established within a random finite set framework.A novel anti-jamming method based on multitarget tracking using probability hypothesis density filters is subsequently developed by combining the characteristic differences between target and jamming with the releasing process of jamming.The characteristic differences between target and jamming and the releasing process of jamming are used to optimize particle partitioning.Particle identity labels that represent the properties of target and jamming are introduced into the detection and tracking processes.The release of cross-eye jamming is detected by estimating the number of targets in the beam,and the distinction between true targets and false jamming is realized through correlation and transmission between labels and estimated states.Thus,accurate tracking of the true targets is achieved under severe jamming conditions.Simulation results showed that the proposed method achieves a minimum delay in detection of cross-eye jamming and an accurate estimation of the target state.展开更多
文摘本文针对复杂背景下红外小目标检测跟踪问题,提出了一种背景自适应的目标检测跟踪方案。针对地面背景下的红外目标检测,采用帧差法,分别提出了跳帧多帧差法和双阈值多帧差法以应对目标长时间静止和灰度对比度下降的问题。针对天空背景下的红外目标检测,采用基于目标区域稳定性和显著性(Regional Stability and Saliency, RSS)的检测算法。在检测得到目标备选点后,使用带标签的高斯混合概率假设密度(Gaussian Mixture Probability Hypothesis Density, GMPHD)滤波器对备选点滤波以输出目标初始轨迹。同时引入轨迹整理将间断的初始轨迹重新连接并进一步去除虚警。经过验证,本文提出的目标检测方法可在复杂多类背景下准确检测并跟踪红外图像中的小目标。
基金Project supported by the National Natural Science Foundation of China(No.61401475)
文摘Cross-eye jamming is an electronic attack technique that induces an angular error in the monopulse radar by artificially creating a false target and deceiving the radar into detecting and tracking it.Presently,there is no effective anti-jamming method to counteract cross-eye jamming.In our study,through detailed analysis of the jamming mechanism,a multi-target model for a cross-eye jamming scenario is established within a random finite set framework.A novel anti-jamming method based on multitarget tracking using probability hypothesis density filters is subsequently developed by combining the characteristic differences between target and jamming with the releasing process of jamming.The characteristic differences between target and jamming and the releasing process of jamming are used to optimize particle partitioning.Particle identity labels that represent the properties of target and jamming are introduced into the detection and tracking processes.The release of cross-eye jamming is detected by estimating the number of targets in the beam,and the distinction between true targets and false jamming is realized through correlation and transmission between labels and estimated states.Thus,accurate tracking of the true targets is achieved under severe jamming conditions.Simulation results showed that the proposed method achieves a minimum delay in detection of cross-eye jamming and an accurate estimation of the target state.
