前视红外系统中复杂背景下典型地物目标跟踪

Object tracking through FLIR based on complicated earth background

前视红外系统主要处理复杂地物背景下的典型地面目标,如桥梁、机场跑道、大型建筑物等。跟踪地面背景较复杂的目标常用的是目标模板匹配的方法。而模板匹配相关跟踪的关键是对实时模板的更新及替换策略。针对前视目标跟踪问题,采用模板相关匹配的方法搜索目标;采用Kalman滤波的方法更新实时模板中的每个像素,以达到更新实时模板的目的,采用Kalman滤波的方法校正跟踪结果坐标位置数据。为了减小运算量同时又不影响跟踪精度,采取了隔若干帧更新一次模板及跟踪位置数据的策略。仿真实验证明,跟踪效果较好。

FLIR mainly treats with the objects such as bridges,airdromes and big buildings etc,which are based on complicated background on earth. The general method for tracking these kinds of targets is correlation matching by standard templates.The key technique of matching in target tracking is how to renew and displace the templates rightly. In this paper, the method of correlation matching is adopted to search targets, Kalman filtering was used to renew every pixels in the templates to be matched and to correct the resulting position of target tracking. To minimize the computing time and insure the precision of tracking at the same time, the templates are renewed and the tracking position is corrected once every several frames.Simulation results show that tracking effect is good.