摘要
针对我国目前对于飞机在地面经常发生的相撞或刮蹭方面的研究较少的现实情况,研究用多传感器数据融合的方法实现飞机的地面防撞。根据现有的多传感器数据融合理论,在分析数据融合过程的基础上,建立混合式数据融合模型,结合模糊神经网络方法实现面向目标的数据融合算法。同时,选用毫米波雷达、红外传感器等多类进行地面多目标的身份识别和威胁评估,从理论上验证了多传感器数据融合思想在飞机地面防撞理论中的可行性,为进一步建立飞机地面防撞系统提供理论基础。
Beacause of less research on aircraft ground collision or scratch in our country, multi-sensor data fusion technology is applied to realize the aircraft ground collision avoidance, According to the present multi-sensor data fusion theory, a combinary model is built on the base of data fusion process analyzing, and a data fusion algrithm is realized by neural network. Besides that, ram-wave radar and infrared sensors are taken as examples to be target identification and danger evaluating data source. The theory is verified to be applicable in aircraft ground collision avoidance, and the theory basement for future aircraft ground collision avoidance system is built.
出处
《测控技术》
CSCD
2008年第6期15-17,共3页
Measurement & Control Technology
基金
中国民航大学科研基金资助项目(07KYM01)
关键词
多传感器
数据融合
防撞
神经网络
威胁估计
multi-sensor
data fusion
collison avoidance
neural network
danger evaluation
