基于低空风预测模型的救援航迹修正规划方法

发布时间：2018-04-21 10:55

  本文选题：空中交通管制 + 低空救援　； 参考：《西南交通大学学报》2016年06期

【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.
[Abstract]:Aiming at the problem that the low altitude rescue track is easy to be affected by crosswind and it is difficult to obtain accurate track planning path, the method of data fusion is used to predict the low altitude wind and to correct the low altitude planning track of aircraft. First of all, the international exchange station in the flight area is used as the observation point. By applying the numerical weather forecast interpretation technology based on the unscented Kalman filter (UKF), the wind speed, wind direction record data of the observation point and the forecast value are fused. A low-altitude wind prediction model is established. Secondly, the system error of the forecast data is corrected by the model, and the modified wind prediction value is obtained. Finally, combining the performance parameters of the aircraft, such as climbing rate, cruise speed, and the wind speed of the passage point, According to the principle of velocity vector synthesis, wind direction information is used to correct the crossing time of each route point. The simulation results show that compared with the traditional Kalman filtering method, the wind speed and wind direction RM_SE predicted by the UKF method are reduced by 12.88% and 17.50%, respectively, and the correction of the initial planned track is more accurate.
【作者单位】： 南京航空航天大学民航学院;
【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)
【分类号】：V355
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本文编号：1782129