基于粒子滤波的空-地目标跟踪算法

针对空-地目标跟踪中目标大幅度变速运动而引 起的跟踪失败问题,基于Kristan等人提出的双步(TS)动态模型框架,对空-地目标跟 踪中目标运动特点进行分析与建模,改进TS模型中 的保守模型以适应加速运动,提出适于描述大幅度变速运动的加速度双步(TSA)动态模型作 为粒子滤波(PF)跟踪算法的动态模 型,实现对粒子状态的精确预测,进而达到使用较少粒子即可对目标鲁棒跟踪的目的。对空 -地目标跟踪的测试视频进行测 试,结果表明,本文算法可对大幅度变速运动目标稳定跟踪,正确跟踪率为92%,对目标 尺寸约为25pixel×30pixel时的处理帧率为29frame/s。本文算法具有较好的鲁棒性与实时性。

Particle filter based algorithm for tracking ground target in airborne environme nt

For the tracking failing caused by target moving in large scale variab le velocity when tracking ground target with the camera in the airborne environment,a two-stage acceleration (TSA) dynamic mode particle filter tracking algorithm is proposed. Based on the framework of the two-stage (TS) dynamic model proposed by Kri stan et al.,the motion features of ground target which is tracked with the camera in the airborne environment are analyzed and modeled. The conservative model of the two-stage (TS) dynamic model is improved to accommodate the accelerated motion.The two-stage acce leration dynamic model which can describe target moving in large scale variable velocity is proposed as the dynamic model of particle filter tracking algorithm,the states of particles can be predicted precisely,and then robust tracking can be realized u sing less particles.The proposed algorithm is tested with video sequences for tracking ground target with the camera in airbo rne environment,and the results show that the proposed algorithm can track ground target moving with large scale variable velo city stability,the accurate rate is 92%,and the average computing frame rate is 29frame/s when the object scale is about 25pix el×130pixel.The algorithm proposed in this paper has better robustness and rea l-time quality.