TCAS Ⅱ与ADS-B数据融合新算法被引量：2

A novel algorithm for TCAS Ⅱ and ADS-B data fusion

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摘要针对空中交通流量越来越大,TCAS Ⅱ无法满足日益增长的防撞需求,提出了根据估计误差协方差最大特征值加权的数据融合算法。该算法首先分析TCAS Ⅱ和ADS-B的原理和特点,阐述了结合ADS-B优势发展组合监视的必要性,重点介绍组合监视区域,采用Kalman滤波对飞机进行目标跟踪,对局部滤波得到的航迹进行加权融合,得到最优估计,对算法进行仿真,结果验证该算法能够得到较高精度数据,提高监视能力,增强防撞性能。 With increasing air traffic flow, TCAS II can＇ t meet growing demand for collision avoidance, data fusion algorithm based on the maximum eigenvalue weighting of estimation error covariance is proposed. Principle and characteristics of TCAS II and ADS-B are analyzed, the necessity of development of combining monitoring combined with advantages of ADS-B is expounded, and combined monitoring area is introduced. Kalman filtering is used for target tracking of aircraft, and the optimal estimation is obtained by weighted fusion of tracks obtained by local filtering. The algorithm is simulated and the results show that the algorithm can get higher precision of data, improve monitoring ability, and enhance performance of collision avoidance.

作者田士佳杨霄鹏姚昆曹逸樵

机构地区空军工程大学信息与导航学院 [

出处《传感器与微系统》 CSCD 2016年第3期130-132,136,共4页 Transducer and Microsystem Technologies

基金国家自然科学基金资助项目(61202490) 航空科学基金资助项目(20150896010)

关键词 TCAS Ⅱ ADS-B 组合监视数据融合卡尔曼滤波 TCAS II ADS-B combined surveillance data fusion Kalman filtering

分类号 V249 [航空宇航科学与技术—飞行器设计]

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