基于子空间的目标跟踪算法研究

Subspace based target tracking algorithm

末制导跟踪阶段,导弹的飞行姿态,弹体与目标的距离以及目标自身的运动姿态和形态均会发生较大的变化,采用单一固定模板无法实现稳定跟踪。本文提出一种新的基于子空间的运动目标跟踪算法,首先采用一组正交的稀疏子空间特征向量表示目标模型,然后采用增量方法不断更新子空间模型,以适应由于目标内在和外在因素所造成的在外观上的变化,从而提高跟踪精度;采用重要性采样算法以及最大似然估计,解决复杂的优化问题。实验结果表明,当摄像机与背景发生较大相对运动以及目标姿态发生剧烈变化时,仍然能够实现对目标的持续稳定跟踪,平均跟踪误差小于10个像素。基本满足末制导跟踪系统的稳定性和鲁棒性等要求。

In terminal guidance tracking phase,the missile＇s flight attitude,the distance from missile to the target and target＇s moving status and appearance change a lot.Using a single fixed template cannot achieve stable tracking.In this paper,a new subspace based moving target tracking algorithm is proposed.First,a set of orthogonalsparse subspace feature vectors are used to describe target model.Then,using incremental method to continuously update the subspace model to accommodate the target changes in appearance which is caused by intrinsic and extrinsic factors,therefore,the tracking accuracy is improved.Finally,importance sampling algorithm and maximum likelihood estimation are applied to solve complex optimization problems.Experimental results show that when the camera and the background suffer larger relative motion and target status changed dramatically,the algorithm can still be able to achieve sustained and stable tracking,and the average tracking error keeps less than 10 pixels.It can satisfy the system requirements of stability and robustness for terminal guidance tracking.