Physics-based forward modeling of edge diffraction scattering centers for complex coated scatterers

Area of Science:

• Electromagnetics and Acoustics
• Computational Physics
• Radar Cross Section (RCS) Analysis

Background:

• Edge diffraction is a key scattering mechanism for low-observable targets, especially those with material coatings.
• Existing scattering center (SC) models lack systematic derivation for complex edges and coatings, hindering accurate parameter characterization.
• Accurate modeling of edge diffraction SCs is vital for understanding and predicting target scattering behavior.

Purpose of the Study:

• To develop an automated forward modeling method for coated edge diffraction SCs.
• To establish a physically interpretable link between edge geometry, material properties, incidence conditions, and SC parameters.
• To enable efficient and accurate characterization of edge diffraction SCs for complex coated scatterers.

Main Methods:

• Utilized the Physical Theory of Diffraction (PTD) to derive spatial radiation expressions for straight and curved edge diffraction SCs.
• Integrated geometric topology and visibility analyses for automatic identification, classification, and separation of effective edge structures.
• Established physical correspondence between target properties (geometry, coating, incidence) and SC parameters.

Main Results:

• Developed a novel, automated method for modeling coated edge diffraction SCs.
• Established a clear physical basis for SC parameter formation, enabling interpretable modeling.
• Demonstrated accurate characterization through comparisons with high-frequency methods and full-wave simulations.

Conclusions:

• The proposed method provides efficient and physically interpretable edge diffraction SC characterization for complex coated targets.
• This facilitates physics-based analysis of target scattering responses, improving low-observable target modeling.
• The approach bridges the gap in systematically deriving SC models from diffraction fields for coated edges.