摘要
针对多个传感器量测航迹在系统误差下关联融合困难的问题,提出基于拓扑4交差模型和三角形拓扑相似度的航迹关联方法,将传感器探测目标分成若干个拓扑三角形结构,使用4交差模型排除不同传感器探测中相关可能性小的三角形;然后定义三角形相似度,对归属于不同探测源的拓扑三角形相似程度进行度量,从而得出目标之间的相关程度,获取航迹关联结果。仿真结果表明,在目标密集编队时,该算法具有有效性。
To solve out the challenges over the track association and fusion with system error when measuring track with multiple sensors,the paper proposes a track association method based on topological 4-intersection-and-difference model and triangle similarity degree.By dividing the detected target of multiple sensors into several topological triangle similarity structures,using 4-intersection-and-difference model,the paper excludes those triangles with small possibility of association ,then the paper defines the triangle similarity degree and measures the topological triangle similarity degree so as to draw the relevance among targets and the result of track association.The simulation result shows,the algorithm is effective in case of intensive formation targets.
出处
《装备学院学报》
2016年第4期69-74,共6页
Journal of Equipment Academy
关键词
航迹融合
航迹关联
拓扑4交差模型
三角形相似度
track fusion
track association
topological 4-intersection-and-difference model
triangle similarity degree
