ADS-B与TCAS II数据融合算法研究

Research on algorithm of ADS-B with TCAS II data fusion

面对空中交通密度越来越大,TCAS II在实际应用中暴露出的虚警和不必要告警等问题愈加明显。为了提供可靠连续的监视信息,提高防撞系统的性能,给出了一种ADS-B与TCAS II组合监视数据融合算法。该算法首先建立了飞机状态空间模型,并分析了ADS-B和TCAS II数据内容和特点,然后研究了数据融合前需要解决的关键问题,利用Kalman滤波器对数据进行处理,采用了在线性最小方差意义下的按标量加权最优信息融合准则和算法对数据进行融合。对该算法进行仿真,结果表明融合后的数据估计误差比任何一个传感器单独估计的误差都要小,说明该算法能够得到较高精度的数据,有效增强了防撞系统的性能。

TCAS II leaking many more obvious problems of false alarm and unnecessary alarm in practical application with the increasing air traffic density, in order to provide the reliable and continuous monitoring information and improve the performance of the anti-collision system, present a data fusion algorithm of the ADS-B with the TCAS II combination monitoring. Firstly, the algorithm establishes the state space model for the aircraft in a reasonable manner, analyses the ADS-B and TCAS II data content and characteristics, and studies the key problems need to be solved before data fusion,using Kalman filter to process data and implement data fusion with the scalar optimal data fusion criterion in the sense of linear minimum variance. Simulate the algorithm and the result shows that the data error after fusion estimation is smaller than any sensor estimation and explains that the algorithm can get high accuracy data, and enhance the performance of the collision avoidance system effectively.