Fast Algorithm for Full-wave EM Scattering Analysis of Large-scale Chaff Cloud with Arbitrary Orientation, Spatial Distribution, and Length

TL;DR

This paper introduces a fast, sparse-structure algorithm for full-wave EM scattering analysis of large-scale chaff clouds, significantly improving speed and memory efficiency while maintaining high accuracy for radar cross section estimation.

Contribution

The paper presents a novel sparsification strategy that simplifies the impedance matrix, enabling faster and more memory-efficient EM scattering analysis of large chaff clouds with arbitrary configurations.

Findings

Algorithm significantly accelerates RCS estimation.

Memory usage is greatly reduced compared to existing methods.

High accuracy is retained in large-scale scenarios.

Abstract

We propose a new fast algorithm optimized for full-wave electromagnetic (EM) scattering analysis of a large-scale cloud of chaffs with arbitrary orientation, spatial distribution, and length. By leveraging the unique EM scattering characteristics in chaff clouds, we introduce the {\it sparsification via neglecting far-field coupling} strategy, which makes an impedance matrix block-banded and sparse and thereby significantly accelerates thin-wire approximate method-of-moments solvers. Our numerical studies demonstrate that the proposed algorithm can estimate the monostatic and bistatic radar cross section (RCS) of large-scale chaff clouds much faster and with greater memory efficiency than the conventional multilevel fast multipole method, while retaining the high accuracy. This algorithm is expected to be highly useful for RCS estimation of large-scale chaff clouds in practical scenarios, serving as a cost-effective ground-truth generator.