飞机位置预测模型的净空区障碍物评定方法  

An Evaluation Method of Clearance Obstacles Based on the Prediction Model of Aircraft Position

作　　者：吴鹏 种小雷[1] 耿昊[1] WU Peng;CHONG Xiaolei;GENG Hao(Aeronautical Engineering College,Air Force Engineering University,Xi＇an 710038,China)

机构地区：[1]空军工程大学航空工程学院,西安710038

出　　处：《空军工程大学学报（自然科学版）》2018年第4期20-24,共5页Journal of Air Force Engineering University(Natural Science Edition)

摘　　要：运用经纬度转换法对收集的飞参数据进行判读处理,为达到国际民航组织提出的飞行时纵向碰撞概率应小于5×10^(-9)的要求,训练BP神经网络用以预测飞机空间位置,在观察纵向偏移分布规律的基础上假定其符合极值Ⅰ型分布,选用K-S检验法进行验证,结合验证的结论建立碰撞风险模型并对机场净空区的障碍物高度对飞行的影响进行风险评定,该文为新建机场选址中的净空条件评定及现有机场净空区的障碍物管理工作提供了一种新的思路和方法。On the basis of aircraft coordinates calculated by latitude and longitude conversion,this paper utilizes the BP neural network for predicting the spatial position of aircraft in accordance with the acceptable level of safety5×10^-9 put forward by the International Civil Aviation Organization.On the basis of observing the longitudinal deviation distribution law,it is assumed that it conforms to the Gumbel distribution and the K-S test method is used for verification.The verification result is then adopted to build a collision risk model for risk assessment of obstacles height in airport clearance.The paper provides a new way to evaluate clearance condition for selecting airport location and administrate obstacles in airport clearance.

关 键 词：机场净空 BP神经网络 碰撞风险模型 

分 类 号：V35[航空宇航科学与技术—人机与环境工程]