ANN-Based Method for Real-Time Recognition of Dielectric Ellipsoid Orientation in 3D Electromagnetic Pulse Scattering

This paper proposes an artificial neural network (ANN)-based method for quickly determining the orientation of a dielectric ellipsoid in 3D electromagnetic pulse scattering. The Method of Auxiliary Sources (MAS) is used to perform the scattering analysis efficiently by handling field singularities and reducing computation time. Gaussian radio pulse serves as the excitation, and the scattered signal is measured at a single observation point. A dataset covering a wide range of orientation angles is used to train the ANN, which accurately estimates the ellipsoid’s orientation with an average error of less than 1° for both angles using just one measurement. This approach is more efficient and practical than conventional radar techniques, especially for real-time applications like target tracking and missile detection. This work presents a significant advance by integrating machine learning with electromagnetic analysis to speed up 3D object recognition.