Application of neuro network modeling for calibration of pyrometric system for unmanned aircraft orientation

Abstract

The paper considers the possibility to calibrate IR sensors in the system for determining the orientation of an unmanned aerial system based on the data of the current meteorological situation using neural network simulation technologies. The results of the study aimed at determining the degree of influence of various meteorological parameters on the output signal of an infrared sensor are presented together with the assessment of the performance of neural networks of various architectures that perform calibration.