Adaptive Algorithm to Improve Trajectory Prediction Accuracy of Climbing Aircraft

Abstract

Aircraft climb trajectories are difficult to predict, and large errors in these predictions reduce the potential operational benefits of some advanced concepts in the Next Generation Air Transportation System. An algorithm that dynamically adjusts modeled aircraft weights based on observed track data to improve the accuracy of trajectory predictions for climbing flights has been developed. In real-time evaluation with actual Fort Worth Center traffic, the algorithm decreased the altitude root-mean-square error by about 20%. It also reduced the root-mean-square error of predicted time at top of climb by the same amount.