Coupled Aerodynamic-Electromagnetic Modeling for RCS Estimation of Million-Scale Chaff Clouds with Arbitrarily Curved 3D Geometries

TL;DR

This paper introduces a coupled aerodynamic-electromagnetic modeling framework that accurately predicts the radar cross section of large-scale, arbitrarily curved chaff clouds by incorporating realistic 3D geometries and their aerodynamic evolution.

Contribution

It extends existing aerodynamic models to include arbitrarily curved 3D chaff geometries and integrates this with a fast electromagnetic solver for real-time RCS estimation of large chaff clouds.

Findings

Aerodynamic effects significantly influence RCS.

Flattened and helical motions affect scattering response.

Framework enables real-time, physically grounded RCS prediction.

Abstract

Accurate prediction of the radar cross section (RCS) of chaff clouds requires careful consideration of aerodynamic effects, as the orientation and spatial distribution of individual chaff elements evolve significantly after deployment. Building upon conventional six-degree-of-freedom (6-DoF) formulations for chaff aerodynamic analysis-which assumed straight or two-dimensionally bent geometries-we extend the framework to incorporate arbitrarily curved three-dimensional chaff geometries. This extension enables accurate modeling of both flattened and helical dynamics induced by aerodynamic moments acting along the roll, pitch, and yaw directions, thereby providing a more comprehensive and realistic description of chaff motion. We then finally develop a coupled aerodynamic-electromagnetic framework that integrates the extended aerodynamic model with our recently developed fast method-of-moments solver, which is optimized for efficiently estimating the RCS of million-scale chaff clouds. The proposed multiphysics coupled framework allows real-time, first-principles prediction of the monostatic and bistatic RCS of large-scale chaff clouds with arbitrary geometries, orientations, and lengths, accurately incorporating their time-varying aerodynamic evolution. Simulation results confirm that the monostatic RCS is strongly influenced by aerodynamic effects, with the coexistence of flattened and helical motions playing a critical role in determining the overall scattering response. The proposed framework thus provides a physically grounded and computationally efficient approach for predicting the RCS of large-scale chaff clouds. Furthermore, it can be directly extended to radar signal processing applications by utilizing multi-frequency complex-valued far-field responses, thereby enabling the reconstruction of Range-Doppler, Range-Angle, and Doppler-Angle maps.