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Modeling and Dynamic Radar Cross-Section Estimation of Chaff Clouds for Real-Time Simulation

Authors :
Jun-Seon Kim
Uk Jin Jung
Su-Hong Park
Dong-Yeob Lee
Moonhong Kim
Dongwoo Sohn
Dong-Wook Seo
Source :
Remote Sensing, Vol 15, Iss 14, p 3587 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Chaff is a passive jammer widely used to disrupt radar or radio-frequency sensors. A mass of chaff fibers dispersed in the air is commonly referred to as a chaff cloud. It is nearly impossible to numerically simulate in real-time the enormous amount of chaff fibers composing the chaff cloud. In this paper, we model the behavior of numerically estimated chaff clouds as probability density functions (PDFs) and apply approximation techniques to estimate the radar cross-section (RCS) of the chaff cloud in real time. To model the aerodynamics of the chaff cloud, we represented the combination of PDFs as functions of time and wind speed. The applied approximation techniques—vector radiative transfer and generalized equivalent conductor method—showed a computation time that cannot be achieved by low-frequency methods such as the method of moments or finite-difference time-domain. Moreover, the dynamic RCS results of the approximation techniques showed a similar trend to those of other studies simulating similar situations. The proposed scheme is effective for real-time chaff cloud simulation, and the modeled dynamics and estimated dynamic RCSs can be a standard baseline for developing new analysis methods for chaff clouds. In the future, the proposed scheme will extend to more chaff fibers and more diverse environmental parameters.

Details

Language :
English
ISSN :
20724292
Volume :
15
Issue :
14
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.f684670d3a2c417e9e5d65493262a430
Document Type :
article
Full Text :
https://doi.org/10.3390/rs15143587