网格聚类在多雷达数据融合算法中的应用

Reasearch on Multiradar Data Fusion Algorithm Based on Grid Clustering

应用网格聚类的方法区分同一雷达接收的不同目标的观测数据,通过类间数据融合,实现同一目标不同雷达接收数据的融合,以便对多目标进行实时跟踪。研究了观测数据网格聚类的基本思想、形式化描述及算法实现,讨论了对机动目标跟踪的Kalman滤波方程及空管系统中易于计算的各参数矩阵理论依据及相应的初值。仿真结果表明,通过网格聚类能很好地区分不同目标,聚类后再进行跟踪融合更加准确。

This paper studies application grid clustering method to distinguish the target observation data which is received by the same radar. The fusion of the same goal＇s observation data received by different radars is realized through the integration of different observation data, so as to realize real-time tracking of multiple targets. The basic thought of grid observation data clustering, and the formal description algorithm are studied. The Kalman filter equations for maneuvering target tracking are described. Parameter matrix theoretical basis for the simplified calculation and the corresponding initial matrix are given for air traffic control system. The simulation result indicates that the grid clustering is able to discriminate different targets well and to carry on the track fusion more accurate.