摘要
针对低空救援航迹易受到侧风影响难以获得准确的航迹规划路径问题,采用数据融合方法预测低空风,修正航空器的低空规划航迹.首先,将飞行区域内的国际交换站作为观测点,通过应用基于无迹卡尔曼滤波(UKF)的数值气象预报释用技术,将观测点的风速、风向记录数据与预报值进行融合,建立低空风预测模型;其次,利用该模型,校正预报数据的系统误差,得出修正的风预测值;最后,结合航空器的爬升率、巡航速度等性能参数与所经航路点的风速、风向信息,依据速度矢量合成原理,修正各航路点的过点时刻.仿真实验表明,与传统的卡尔曼滤波预测方法相比,由UKF方法预测得到的风速、风向RM_SE分别减少了12.88%与17.50%,对初始规划航迹的修正更为精确.
Considering that an accurate rescue trajectory is hard to obtain in low altitude and crosswind conditions, the data fusion technique was employed to predict the wind condition at low altitude and, accordingly, to amend the low-trajectory rescue trajectory plan for the aircraft. Taking the international exchange stations within the flying area as the observation points, the numerical weather prediction and interpretation technology based on the unscented Kalman filtering （UKF） was used to build a low-level wind forecasting model by combing the record data sets of wind velocities and directions from the observation points and prediction data sets. Then, the model was used to correct the system error in the original prediction data and produce the modified prediction values about the wind. Finally, according to the principle of velocity triangle, performance parameters such as the rate of climb, cruise speed of the aircraft were combined to estimate the passing time of aircraft at each waypoint. Simulation shows that compared with the results obtained by the traditional Kalman filtering, the root mean square errors of wind speed and wind direction by UKF are decreased by 12.88% and 12.88% ; and the initially planned trajectory can be modified more accurately.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2016年第6期1258-1264,共7页
Journal of Southwest Jiaotong University
基金
国家自然科学基金资助项目(U1233101
71271113
U1633119)
中央高校基本科研业务费专项基金资助项目(NS2016062)
关键词
空中交通管制
低空救援
航迹
气象预测
无迹卡尔曼滤波
air traffic control
low altitude rescue
trajectory
weather forecasting
unscentedKalman filtering
