CAJ | 학술논문

航空器预计到达时刻（ ETA）是航空器进场排序与调度的基础，因此进场航空器飞行时间的快速与准确预测显得尤为重要。基于历史雷达轨迹分析，通过RBF（ Radial Basic Function ）神经网络构建进场航空器进港时的高度、速度、进场飞行距离与进场飞行时间的映射关系，利用正交最小二乘算法设计基于RBF神经网络的进场飞行时间预测模型。以上海浦东机场VMB进港点进场航班为例进行仿真验证，在考虑航空器机型的情况下，可将航空器飞行时间预测的均方根误差控制在50 s以内。仿真结果表明，提出的方法能够有效地实现进场飞行时间的快速与准确预测。
항공기예계도체시각（ ETA）시항공기진장배서여조도적기출，인차진장항공기비행시간적쾌속여준학예측현득우위중요。기우역사뢰체궤적분석，통과RBF（ Radial Basic Function ）신경망락구건진장항공기진항시적고도、속도、진장비행거리여진장비행시간적영사관계，이용정교최소이승산법설계기우RBF신경망락적진장비행시간예측모형。이상해포동궤장VMB진항점진장항반위례진행방진험증，재고필항공기궤형적정황하，가장항공기비행시간예측적균방근오차공제재50 s이내。방진결과표명，제출적방법능구유효지실현진장비행시간적쾌속여준학예측。
Estimated Time of Arrival ( ETA ) plays a great role in arrival sequencing and scheduling , therefore it is particularly important to predict the arrival flight time quickly and accurately .Based on the analysis of historical radar track ,with the help of RBF ( Radial Basic Function ) Neural Network ,the map-ping relationship is constructed between the arrival aircraft′s altitude/speed at the metering point ,flight distances and flight time .And then,the orthogonal least squares ( OLS) algorithm is adopted to design the RBF-NN based arrival flight time prediction model .Taking the arrival aircrafts via VMB to Shanghai Pud-ong Airport as examples ,the RMSE between estimated and actual time of arrival is controlled within 50 s with consideration of the same aircraft type .The simulation results indicated that the proposed approach is able to predict arrival flight time quickly and accurately .