New Multiple-Target Tracking Strategy Using Domain Knowledge and Optimization
提出一种利用领域知识的环境依赖车辆动态建模方法，并基于此开发了领域知识辅助的移动视界估计方法，用于地面移动目标跟踪，在杂波环境中结合多假设跟踪结构解决数据关联模糊问题。
This paper proposes an environment-dependent vehicle dynamic modeling approach considering interactions between the noisy control input of a dynamic model and the environment in order to make best use of domain knowledge. Based on this modeling, a new domain knowledge-aided moving horizon estimation (DMHE) method is proposed for ground moving target tracking. The proposed method incorporates different types of domain knowledge in the estimation process considering both environmental physical constraints and interaction behaviors between targets and the environment. Furthermore, in order to deal with a data association ambiguity problem of multiple-target tracking in a cluttered environment, the DMHE is combined with a multiple-hypothesis tracking structure. Numerical simulation results show that the proposed DMHE-based method and its extension could achieve better performance than traditional tracking methods which utilize no domain knowledge or simple physical constraint information only.