基于区间动态划分的DP-TBD算法

DP-TBD Algorithm Based on Interval Dynamic Partitioning

检测前跟踪(track before detect,TBD)算法可在低信杂比和低信噪比环境中对微弱目标进行检测和跟踪,但由于其保留全部原始数据而很难应用于对实时性要求较高的雷达系统。文中基于传统的单目标DP-TBD算法,利用DBSCAN聚类和两点起始对量测区间进行动态划分,降低量测区域较大、分辨单元较多带来的严重计算负担。经仿真验证,提出算法在运算效率和跟踪性能上较传统算法均有所提高。

The track before detect(TBD)can effectively detect and track weak target in a low signal to clutter and signal to noise ratio environment,however,because it retains all the raw data,it is difficult to apply in radar systems with high requirements for real-time processing.To solve the above issues,based on the traditional single target DP-TBD algorithm,dynamic partitioning of measurement intervals using DBSCAN and two-point trace start is proposed in this paper,to reduce the serious calculation burden which caused by large measurement area is and more resolution units.Simulation results show that the proposed algorithm has high computational efficiency and high tracking performance.