A real-time vision prediction algorithm for aviation track of unmanned air vehicle

Aiming at the practical background of less data and unknown probability distribution, the metabolic GM(1,1) model was proposed to predict the aviation location of mobile target such as unmanned air vehicle in the electronic information equipment test. The prediction principle of the metabolic GM(1,1) model was introduced firstly. The new location information was reinforced and the old location information was deleted in the modeling process constantly. So the higher prediction precision could be obtained. And then the prediction method was simulated and validated through the aviation data of an unmanned air vehicle. The simulation results show that the proposed approach is feasible and effective. It can not only predict the location information of the next period with high prediction precision, but also can obtain the location information of any time in the period.