关于UKF方法的新探索及其在目标跟踪方面的应用

New development of UKF and its applications in target tracking on re-entry

在跟踪和控制领域,和被广泛采用的推广卡尔曼滤波(extended Kalman filter)方法相比较,近年发展起来的Unscented卡尔曼滤波(Unscented Kalman filter)具有易于实现、计算量相当而精度较高等诸多优点．本文深入探讨了这一方法,并以目标跟踪为背景,提出了两种基于Unscented变换的新的滤波方法,分别在算法的精确和快速两个方向上进行了尝试,仿真结果表明,这种探索是行之有效的．

Compared with the widely used extended Kalman filter （EKF） in tracking and control community, the advantages of recently developed filtering algorithm called Unscented Kalman filter are significant with its ease to tune, better accuracy and same order of computational complexity. Based on the Unscented transformation, two new filtering algorithms are presented, intending to improve the precision and to raise the speed respectively. Performance and implementation in target tracking on reentry show their efficiency.