基于D-S证据理论的无源航迹关联算法

Track association algorithm with multi-feature based on distributed multi-target passive tracking system

摘要:

目前分布式无源多目标跟踪系统的航迹关联算法基本照搬多传感器数据融合的理论，仅利用目标的状态信息。文中利用了目标的多特征信息(载频、脉宽、脉冲重复间隔(PRI)等)，应用Dempster-Shafer(D-S)证据理论，提出了一种基于分布式无源多目标跟踪系统的多特征信息融合航迹关联算法。算法具有以下优点：关联速度快，正确率高，而且能够适应密集目标的环境。仿真实验证明该算法的航迹关联效果明显优于加权航迹关联算法。

Abstract:

Present track association algorithms in distributed multi-target passive tracking system always adopt theory in multi-sensor information fusion, in other words, only state informations of targets are concerned. A new track association algorithm is proposed based on information fusion of multi-feature such as frequency pulse-width and Pulse Repetition Interval(PRI) in distributed multi-target passive tracking system by applying Dempster-Shafer(D-S) evidence theory. The algorithm is of such advantages like faster association speed, higher correctness probability and it can be adapted to circumstance of dense targets due to the use of multi-feature information. The simulation proves that the proposed algorithm is superior to weighted track association.