基于VSIMM-SRCKF的ADS-B航迹滤波方法研究  

Research on ADS-B track filter method based on VSIMM-SRCKF

作　　者：杜云 张静怡 DU Yun;ZHANG Jingyi(School of Electrical Engineering,Hebei University of Science and Technology,Shijiazhuang,Hebei 050018,China)

机构地区：[1]河北科技大学电气工程学院,河北石家庄050018

出　　处：《河北工业科技》2020年第1期17-22,共6页Hebei Journal of Industrial Science and Technology

基　　金：河北科技大学校立科研基金(2014PT27);河北省通用航空增材制造协同创新中心开放基金。

摘　　要：为了提高ADS-B航迹跟踪精度,并针对交互多模型算法所选模型集而导致的跟踪性能下降的问题,采用基于平方根容积卡尔曼的变结构交互多模型(VSIMM-SRCKF)算法对航迹进行滤波。建立运动目标跟踪的VSIMM模型集来描述机动目标的系统总模型集合,在滤波过程中,SRCKF递推的更新通过将协方差矩阵开平方得到,使计算复杂度降低,并且使协方差矩阵保持非负定,能够避免滤波中的发散问题。仿真结果表明:提出的基于平方根容积卡尔曼的变结构交互多模型算法(VSIMM-SRCKF)在估计误差均值、估计误差标准差以及平均绝对百分比误差方面均优于IMM-CKF算法和IMM-SRCKF算法,说明VSIMM-SRCKF算法具有更好的跟踪精度,可适应于复杂目标航迹的实时跟踪。In order to improve the tracking accuracy of ADS-B,and to address the problem of tracking performance degradation caused by the interactive multi-model algorithm depending on the selected model set.In this paper,the variable structure interactive multiple model(VSIMM-SRCKF)algorithm based on the square root volume Kalman is used to filter the flight path.Firstly,a VSIMM model set for moving target tracking is established to describe the total system model set of the maneuvering target.During the filtering process,the recursive update of SRCKF is obtained by squaring the covariance matrix,which reduces the computational complexity and keeps the covariance matrix non-negative definite,which successfully avoids the divergence problem in filtering.The simulation results show that the variable structure interactive multi-model algorithm(VSIMM-SRCKF)based on the square root volume Kalman is better than the IMM-CKF algorithm and the IMM-SRCKF in terms of the estimated error mean,estimated error standard deviation,and average absolute percentage error.The algorithm shows that the VSIMM-SRCKF algorithm has better tracking accuracy and can be adapted to the real-time tracking of complex target tracks.

关 键 词：算法理论 ADS-B 航迹滤波 变结构交互多模型 平方根卡尔曼滤波器 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] V355.1[自动化与计算机技术—控制科学与工程]