A Classifying-Inversion Method of Offshore Atmospheric Duct Parameters Using AIS Data Based on Artificial Intelligence

Atmospheric duct parameters inversion is an important aspect of microwave-band radar and communication system performance evaluation. AIS (Automatic Identification System) one the signal sources used for atmospheric inversion. Before parameters, determining type plays role in results, but current methods ignore this point. We outlined a classifying-inversion method using signals combined with artificial intelligence. The consists classification model parameter model. judges duct, inverts according to duct. Our findings demonstrated that accuracy based on deep neural network (DNN) even exceeds 97%, has better than traditional method, thereby illustrating effectiveness novel method.