Classification and Prediction of RF Coupling Inside A-320 and A-319 Airplanes using Feed Forward Neural Networks

Neural network modeling is introduced in this paper to classify and predict interference path loss measurements on Airbus 319 and 320 airplanes. Interference patterns inside the aircraft are classified and predicted based on the locations of the doors, windows, aircraft structures and the communication/navigation system-of-concern. Modeled results are compared with measured data and a plan is proposed to enhance the modeling for better prediction of electromagnetic coupling problems inside aircraft