A neural-based method of determining aircraft landing paths from DTED

This paper describes a method of employing neural networks to determine the correct landing approach from digital terrain elevation data (DTED) with and without onboard sensors. Our objective is to improve the safety of aircraft landing systems chat rely on instrument flight rating (IFR). The neural network paradigm described in this paper consists of two tests. The first is the determination of the correct flight path from DTED alone. The second compares results from aircraft sensors to a known set of terrain statistics. In tiffs case the aircraft data is synthesized but characteristics from similar airports have been calculated and should provide a reasonable approximation. One of the objectives of this work is to resolve the required distance for determination of whether the aircraft is on the proper approach. Another objective is to discern where the aircraft is actually located. The end result is a system that warns pilots of impending danger directly related to inaccurate positioning.