Behavior pattern mining based on spatiotemporal trajectory multidimensional information fusion  

作　　者：Qiaowen JIANG Yu LIU Ziran DING Shun SUN 

机构地区：[1]Institute of Information Fusion,Naval Aviation University,Yantai 264001,China [2]Department of Electronic Engineering,Tsinghua University,Yantai 100083,China

出　　处：《Chinese Journal of Aeronautics》2023年第4期387-399,共13页中国航空学报（英文版）

基　　金：co-supported by the National Key R&D Program of China(No.2021YFA0715202);the National Natural Science Foundation of China(Nos.62022092,61790550,62171453);the Outstanding Youth Innovation Team Program of University in Shandong Province,China(No.2021KJ005).

摘　　要：Trajectory data mining is widely used in military and civil applications,such as early warning and surveillance system,intelligent traffic system and so on.Through trajectory similarity measurement and clustering,target behavior patterns can be found from massive spatiotemporal trajectory data.In order to mine frequent behaviors of targets from complex historical trajectory data,a behavior pattern mining algorithm based on spatiotemporal trajectory multidimensional information fusion is proposed in this paper.Firstly,spatial–temporal Hausdorff distance is pro-posed to measure multidimensional information differences of spatiotemporal trajectories,which can distinguish the behaviors with similar location but different course and velocity.On this basis,by combining the idea of k-nearest neighbor and density peak clustering,a new trajectory clustering algorithm is proposed to mine behavior patterns from trajectory data with uneven density distribu-tion.Finally,we implement the proposed algorithm in simulated and radar measured trajectory data respectively.The experimental results show that the proposed algorithm can mine target behavior patterns from different complex application scenarios more quickly and accurately com-pared to the existing methods,which has a good application prospect in intelligent monitoring tasks.

关 键 词：Behavior pattern Hausdorff distance Information fusion Spatiotemporal trajectory Trajectory clustering 

分 类 号：V355[航空宇航科学与技术—人机与环境工程]