一种基于ADS-B的雷达误差实时融合校正算法  

ADS-B-Based Algorithm for Real-Time Optimal Estimation of Radar Biases

作　　者：吴振亚[1,2] 王明辉[1] 张瑞平 阿都建华[1] 胡俊[4] 

机构地区：[1]四川大学计算机学院,四川成都610065 [2]民航局第二研究所,四川成都610041 [3]民航西南地区空中交通管理局,四川成都610202 [4]成都师范学院计算机系,四川成都611130

出　　处：《西南交通大学学报》2013年第1期102-106,115,共6页Journal of Southwest Jiaotong University

基　　金：国家自然科学基金资助项目(60736045)

摘　　要：针对我国中西部地区雷达未实现多重覆盖,大部分飞机未配备广播式自动相关监视(automatic dependentsurveillance-broadcast,ADS-B)机载设备,监视精度不高的问题,结合雷达误差模型理论,提出了基于ADS-B数据的雷达误差实时校正算法.该算法对同一时刻获得的多组ADS-B数据与雷达数据的差值进行数据融合,得到该时刻雷达误差的最优估计值,并对雷达进行误差校正.算例仿真结果表明:经该算法校正后,雷达测量的距离与真实距离之间的均方根误差约为50 m,测量的角度与真实角度之间的均方根误差约为0.04°,且校正后的航迹和真实飞行航迹基本重合.In order to improve the surveillance accuracy of radars in China＇s central and western regions, where multiple coverage does not come true and majority airplanes are not equipped with ADS- B （automatic dependent surveillance-broadcast ）, an ADS-B-based algorithm for real-time optimal estimation of radar biases was proposed on the basis of the radar biases theory. The algorithm can achieve a real-time optimal estimation of radar biases by the data fusion based on the difference between ADS-B data and radar data at the same time as well as the real-time calibration of the radar. The simulation of a case study shows that the root mean square of biases between calibrated and real range values is about 50 m, the root mean square of biases between calibrated and real angle values is about 0.04°, and the calibrated radar trajectories are essentially coincident with actual trajectories.

关 键 词：ADS—B 数据融合 实时校正 卡尔曼滤波 雷达 航迹跟踪 

分 类 号：TN953[电子电信—信号与信息处理]