基于多特征融合的微弱红外运动目标跟踪方法  

Infrared dim moving target tracking method based on multiple features

作　　者：李正周[1] 马齐佑[1] 郑微[1] 刘书君[1] 金钢[2,3] 

机构地区：[1]重庆大学通信工程学院,重庆400044 [2]中国空气动力研究与发展中心,四川绵阳621000 [3]中国科学院光电技术研究所,成都610209

出　　处：《强激光与粒子束》2011年第1期54-58,共5页High Power Laser and Particle Beams

基　　金：中央高校基本科研业务费资助课题(CDJZR10160004)

摘　　要：利用红外跟踪测量系统能够同时获取目标运动信息(包括方位角、俯仰角以及角速度)、目标信号幅度及其成像面积等,提出了一种基于多特征融合的弱红外运动目标跟踪方法。分析了红外成像系统中目标信号特点,得到目标的运动、幅度和面积具有一致性和连续性,符合高斯分布;采用概率数据关联滤波推导量测各特征的关联概率,并根据特征的波动状况确定多特征融合的加权系数,估计和更新目标运动状态。理论分析和实验结果表明:该方法的跟踪精度和稳定性都明显高于仅依靠运动特征关联和依靠运动特征和幅度特征关联的跟踪方法。Based on the fact that the motion（i.e.azimuth,elevation and their derivative velocities）,amplitude and size of infrared target could be acquired simultaneously,a multi-feature association based approach is presented to track infrared dim moving target.The characters of the infrared imaging tracking system are first analyzed,and the motion,amplitude and size of target of interest are modeled as second order stationary random signals.The probability of motion,amplitude and size of measurement originated as target of interest is then estimated by Gaussian distribution.Subsequently,the combined probability of motion,amplitude and size is derived by probabilistic data association（PDA）,and their weight coefficients are estimated adaptively according to their fluctuations.Finally,the relevant parameters including combination measurement are predicted and updated.Some experiments are included and the results show that the performance of target tracking is significantly enhanced by the proposed approach.

关 键 词：微弱红外目标 运动目标跟踪 概率数据关联滤波 多特征融合 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]