基于目标之间拓扑信息的数据关联方法

数据关联是多平台多源信息融合系统中的关键问题。当传感器平台高速移动时,其自身的定姿定位往往存在一定误差,此时多个传感器对同一目标形成的量测经过坐标转换到同一坐标系下后会存在很大偏差,通过目标位置、速度等信息进行关联难度较大。所以,尝试提取目标的另一特征—目标之间的拓扑信息,通过对目标之间的拓扑信息进行模糊匹配和搜索,找到最佳的关联拓扑组,为数据关联和配准提供进一步校准的先验信息。仿真实验表明该方法具有较高的关联精度和鲁棒性。

Data Association Based on Target Topology

Data association is a key problem in multiple-sensor multiple-target tracking. Normally, there is bias of location while the platform of sensor is moving. In that case, the measurement for the same target from multiple sensors will have a large bias through coordinate transforming. It is a boring problem for utilizing position and velocity of target to associate. In order to solve this problem, topological information of targets was abstracted. And based on them, through matching and searching, an optimal topological pair was obtained. Then this topological pair was provided to prior information for data association and marching. The simulations show that this method has better accuracy and robusticity.