Analyzing and Evaluating Aircraft Prediction Models based on Automatic Targets with Unidentified Orientation Data

Abstract

The aircraft prediction model has been developed to identify the type and model of aircraft based on unknown target data. This serves as a crucial factor in military strategic decision-making to gain a tactical advantage. The essential aircraft types encompass fighters, transporters, helicopters, and training aircraft. These aircraft types have the capability to cause harm and pose a threat to national security when identified as unidentified targets on radar screens. Each type of aircraft encompasses various models, each with distinct capabilities tailored for different mission profiles, such as long-range flight, cargo transport, bombing, attack, and reconnaissance. For this reason, effective air defense necessitates the accurate identification of aircraft types and models, enabling strategic decision-making for appropriate response strategies. Although there have been studies on constructing aircraft prediction models from past research, it was found that they primarily focused on predicting types or specific models of aircraft, revealing limitations in their practical application. Therefore, the aircraft prediction model is imperative to be considered based on methods that align with the requirements for identifying the type and model of aircraft. This research conducts an evaluation and analysis of an aircraft prediction model generated using contemporary methods, employing a diverse set of procedural steps to identify the type and model of aircraft. This is done to pinpoint and advocate the use of suitable and efficient procedural steps.