Anisotropic Scatterer Models for Representing RCS of Complex Objects

Eric Huang, Coleman Delude, Justin Romberg, Saibal Mukhopadhyay, Madhavan Swaminathan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

The need to simulate complex electromagnetic (EM) wave interactions by multiple radar targets, transmitters, and receivers to better study the performance of radar systems, antenna designs, and/or stealth technologies has grown over time. High performance computing (HPC) based emulators can be used to model the scattering from multiple stationary and moving targets for radar applications. These emulators rely on the Radar Cross Section (RCS) of the targets being available in complex scenarios. Representing the RCS using tables generated from EM simulations is often times cumbersome leading to large storage requirement. An alternative approach is to represent the targets as a collection of isotropic or anisotropic scatterers. In this paper we present a method to represent the RCS of complex targets using a 3D anisotropic scatterer model, where we use the analytical RCS representation of a large ellipsoid as the basis function to determine the angular dependency of the RCS from each scatterer. The scatterer model that best represents the RCS data is obtained by solving a least square inverse problem. To improve the correlation with EM solvers, we further break down the optimization problem by considering shadowing effect and use multiple models, each representing a subset of the RCS data. The results show that the scatterer model can effectively represent the RCS data of complex targets.

Original languageEnglish (US)
Title of host publication2021 IEEE Radar Conference
Subtitle of host publicationRadar on the Move, RadarConf 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728176093
DOIs
StatePublished - May 7 2021
Event2021 IEEE Radar Conference, RadarConf 2021 - Atlanta, United States
Duration: May 8 2021May 14 2021

Publication series

NameIEEE National Radar Conference - Proceedings
Volume2021-May
ISSN (Print)1097-5659

Conference

Conference2021 IEEE Radar Conference, RadarConf 2021
Country/TerritoryUnited States
CityAtlanta
Period5/8/215/14/21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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