Abstract
This study proposes a low-altitude wind prediction model for correcting the flight path plans of low-altitude aircraft. To solve large errors in numerical weather prediction (NWP) data and the inapplicability of high-altitude meteorological data to low altitude conditions, the model fuses the low-altitude lattice prediction data and the observation data of a specified ground international exchange station through the unscented Kalman filter (UKF)-based NWP interpretation technology to acquire the predicted low-altitude wind data. Subsequently, the model corrects the arrival times at the route points by combining the performance parameters of the aircraft according to the principle of velocity vector composition. Simulation experiment shows that the RMSEs of wind speed and direction acquired with the UKF prediction method are reduced by 12.88% and 17.50%, respectively, compared with the values obtained with the traditional Kalman filter prediction method. The proposed prediction model thus improves the accuracy of flight path planning in terms of time and space.
Highlights
With its advantages of wide rescue range, fast response, and small restriction by geographical factors, air emergency rescue plays an irreplaceable role in preventing and reducing disasters in many countries
In order to keep a safe separation of other aircraft and reduce the probability of the conflict, the focus is on making a precise flight path planning of every aircraft based on the rescue task
The planned flight path of an aircraft should keep a safe separation of other aircraft in a low-altitude environment
Summary
With its advantages of wide rescue range, fast response, and small restriction by geographical factors, air emergency rescue plays an irreplaceable role in preventing and reducing disasters in many countries. Considering the influence of meteorological conditions on flights is an effective measure to improve the authenticity of path planning [1]; the key is accurately predicting low-altitude wind, as well as analyzing aircraft motion in the wind field. The method proposed in the present study acquires the predicted values at any point on the flight route with a spatial interpolation model to overcome the problem in which NWP data are located in a particular lattice. To solve the large errors of NWP data and the inapplicability of high-altitude meteorological data to low-altitude conditions, the proposed method fuses the low-altitude lattice prediction data and observation data of a specified ground international exchange station through the unscented Kalman filter (UKF)-based NWP interpretation technology to acquire the predicted low-altitude wind data. Because the earth is an approximate sphere, this hexahedron is not a cuboid
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