航空器4D航迹目标跟踪精度设计研究  

Design and Research on Tracking Accuracy of 4D Trajectory of Aircraft

作　　者：杜实[1] 任景瑞[1] 郭嘉 DU Shi;REN Jing-rui;GUO Jia(College of Air Traffic Management,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学空中交通管理学院

出　　处：《计算机仿真》2019年第5期38-41,77,共5页Computer Simulation

基　　金：中央高校基本科研业务费项目中国民航大学专项资助(3122017068)

摘　　要：航空器航迹跟踪精度直接关系到是否满足基于轨迹运行的实时跟踪业务需求,针对航空器的四维航迹跟踪分析中涉及参数过多的问题,采用最近邻域关联滤波算法以及传统的概率数据关联算法与卡尔曼滤波算法结合的概率数据关联滤波算法对航空器运行过程中的时间、三维位置及速度进行跟踪精度设计,并且使用MATLAB仿真软件进行了理论仿真及分析。通过对同一航迹进行跟踪分析,比较两种算法在三个不同方向上的位置及速度上的跟踪情况,滤波误差均值,取误差均值较小者为优。仿真结果表明,上述两种算法都能够对航迹进行较好地跟踪,并且可以满足基于轨迹运行的业务需求。Aircraft tracking accuracy is directly related to whether or not to meet the needs of real-time tracking business based on trajectory.In view of the problem of excessive parameters involved in the four-dimensional trajectory tracking analysis of aircraft,the nearest neighbor correlation filtering(NNCF) algorithm and the traditional probabilistic data association algorithm Kalman filter algorithm were combined with probability data association filtering(PDAF) algorithm for aircraft operation time,three-dimensional position and velocity tracking accuracy design,and the MATLAB simulation software was used for theoretical simulation and analysis.By tracking and analyzing the same track,the tracking and filtering of the position and speed of the two algorithms in three different directions were compared,and the mean value of the filtering error was taken as the best.The simulation results show that both of these algorithms can track the trajectory well,and can meet the business needs of trajectory-based operation.

关 键 词：四维航迹 航迹跟踪 航迹融合 最近邻域关联滤波 概率数据关联滤波 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]