A flight path planning method based on improved artificial potential field

With the increasing number of long range free flight, the flight path planning becomes an important issue. In this paper, the expected path is defined as linear potential field. The trajectory equation to determine maximum likelihood flight heading is established by calculating aircraft potential field gravitation of the trajectory at any space position. The air speed degradation model is built by the analysis of the upper air wind influence, and the distance cost can be defined at any position by taking flight performance constraints into consideration. Finally, an optimization model of flight path is established, which selects distance cost and simplicity as the optimization targets, and an ant colony algorithm is proposed. Many groups of flight paths from the Pareto ant colony algorithm are conducive to collaborative decision scientifically and rationally. Experimental results verify the validity of the method.