多目标跟踪的扩展统一方法

E. Emre, J. Seo
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引用次数: 1

摘要

通过对多目标跟踪(MTT)的全局建模,可以利用系统辨识技术同时解决数据关联和机动估计问题。利用这种方法,以前开发的单目标跟踪-加速度估计技术也可以直接用于MTT问题。特别是多模型(自适应)卡尔曼滤波(MMKF)可以得到最优解。出于计算考虑,可以应用MMKF的一些次优解,如一步条件最大似然或最大后验估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An extended unifying approach to multi-target tracking
By means of global modeling of multitarget tracking (MTT), data-association and maneuver-estimation problems can be simultaneously solved using system identification techniques. With this approach, previously developed single-target tracking-acceleration estimation techniques can also be directly used for the MTT problem. In particular multiple-model (adaptive) Kalman filtering (MMKF) can be used to obtain the optimal solution. For computational considerations, one can apply some suboptimal solutions of MMKF such as one-step conditional maximum likelihood or maximum posteriori estimation.<>
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