摘要
研究低信噪比复杂背景下的红外弱小目标检测和跟踪问题。基于多特征融合的小目标检测算法具有较好的检测性能和适应性,而粒子滤波则是一种处理非线性和非高斯动态系统状态估计的有效方法。结合两种算法的优点,提出了一种基于多特征融合与粒子滤波的红外弱小目标跟踪方法。仿真试验表明,与单特征跟踪算法相比,该算法对复杂背景下的红外弱小目标具有更好的跟踪与检测性能。
The problem of detecting and tracking small targets in a sequence of infrared images with very low SNR was studied. The detecting algorithm based on multi-feature fusion is robust and efficient, and the particle filter is an effective method for state estimation in non-linear and non-Gaussian dynamic systems. A method of target tracking in infrared image sequences based on particle filter and multi-feature fusion was presented. Compared with single-feature tracking method, the tracking result shows that the algorithm has strong ability of detecting and tracking under clutter background.
出处
《弹箭与制导学报》
CSCD
北大核心
2009年第5期304-307,共4页
Journal of Projectiles,Rockets,Missiles and Guidance
关键词
红外弱小目标
多特征融合
粒子滤波
目标跟踪
small infrared target
multi-feature fusion
particle filter
target tracking
