摘要
列车防撞辅助预警系统是在列车自动防护系统失效情况下保障列车行车安全的重要系统之一,该系统基于二次雷达的测距原理进行列车间的测距和预警,其测距精度直接影响系统的可靠性。针对列车防撞辅助预警系统基于二次雷达的测距数据含有较大噪声的问题,本文基于离散线性系统理论,建立测距数据的离散线性系统模型,获取离散线性卡尔曼滤波参数,然后对测距数据进行滤波处理。通过使用MATLAB对静态和动态测距数据进行卡尔曼滤波仿真试验,证实卡尔曼滤波可将测距数据的噪声降低50%以上,并且不会产生数据延时,提高系统的可靠性。
Train anti-collision auxiliary early warning system is one of the important systems to ensure the safety of train operation in case of failure of the automatic train protection system.Based on the principle of the secondary surveillance radar ranging,the system performs ranging and anti-collision warning between trains,and its ranging accuracy directly affects the reliability of the system.In view of the problem that the secondary surveillance radar ranging data of the train anti-collision auxiliary early warning system is easy to be interfered by the NLOS and contains a lot of noise,this paper,based on the theory of discrete linear system,establishes the discrete linear system model of ranging data,analyzes the discrete linear Kalman filter parameters,and then filters the ranging data.Through the Kalman filter simulation test of ranging data,it is confirmed that the Kalman filter can reduce the noise of ranging data by more than 50%without data delay,and improve the reliability of the system.
作者
杨玉钊
郑良广
YANG Yu-zhao;ZHENG Liang-guang(Ningbo CRRC Times Transducer Technology Co.,Ltd.,Ningbo 315020,China)
出处
《电子设计工程》
2020年第18期56-59,共4页
Electronic Design Engineering
关键词
噪声
卡尔曼滤波
列车防撞辅助预警系统
测距
noise
Kalman filter
train anti-collision auxiliary early warning system
ranging
