On Modeling RCS of Aircraft for Flight Simulation

Persson, Björn; Norsell, Martin

doi:10.1109/map.2014.6931656

Cited by 19 publications

(11 citation statements)

References 11 publications

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“…Highresolution RCS mat rices, generated using Physical Opt ics (PO) were used in an investigation of RCS matrix resolution. In [50] accuracy dependent problems use RCS interpolation that is obtained fro m spline appro ximat ions. Co mputational cost dependent PO Problems use bilinear interpolation with compro mise in accuracy.…”

Section: Po (Physical Optics)mentioning

confidence: 99%

Review on Computational Electromagnetics

Sumithra

Thiripurasundari²

2017

AEM

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Co mputational electro magnetics (CEM) is applied to model the interaction of electro magnetic fields with the objects like antenna, waveguides, aircraft and their environment using Maxwell equations. In this paper the strength and weakness of various computational electromagnetic techniques are deliberated in detail. Performance of various techniques in terms accuracy, memory and co mputation time for application specific tasks such as modeling RCS (Radar Cross Section), space Applications, thin wires and antenna arrays are presented in this paper. Co mmercial software codes has certain limitations, Agilent ADS could not model 3D structures, HFSS is accurate but execution time is h igh, WIPL-D ® does not support modeling Inhomogeneous dielectrics embedded metal objects and periodic structures. IE3D ® is not suited for geometry with fin ite details. However for regular shapes like rectangular patch MOM based IE3D provides accurate results than FEM based IE3D. The co mp licated structures are dealt with accuracy by using CST Microwave Studio ® and HFSS ® . Although CST and HFSS has similar interface in dealing with geo metry with fine details, CST had edge over HFSS software as it starts in time do main and ends in frequency domain. HFSS uses Finite Element Method (FEM ) to arrive at frequency domain solution. FEKO ® has two main solvers MOM based and GTD based. GTD based FEKO is good in handling large structures like reflector antennas.

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Section: Po (Physical Optics)mentioning

confidence: 99%

Review on Computational Electromagnetics

Sumithra

Thiripurasundari²

2017

AEM

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“…(v) Calculate the relative interpolation error ε in R max using (9). (vi) Present the interpolation error in the form of a box plot for comparison of accuracy.…”

Section: Evaluation Of Sampling Schemesmentioning

confidence: 99%

“…For complex targets, such as ships, tanks, and aircraft, it is often only possible to estimate the RCS value at discrete electromagnetic configurations, whereas, for many applications, continuous RCS models are desired. Such continuity is achieved by systematically calculating the RCS values and interpolating to obtain values between the samples [8][9][10]. This work aims to investigate and analyze the possibility of decreasing the number of samples required, while maintaining the same interpolation accuracy, by applying alternative RCS sampling schemes.…”

Section: Introductionmentioning

confidence: 99%

Reduction of RCS Samples Using the Cubed Sphere Sampling Scheme

Persson¹,

Norsell²

2016

PIER M

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Abstract-An alternative to the traditional method of sampling radar cross section data from measurements or electromagnetic code is presented and evaluated. The Cubed Sphere sampling scheme solves the problem of oversampling at high and low elevation angles and at equal equatorial resolution the scheme can reduce the number of samples required by approximately 25%. The analysis is made of an aircraft model with a monostatic radar cross section at C-band and a bistatic radar cross section at VHF-band, using Physical Optics and the Multilevel Fast Multipole Method, respectively. It was found that for the monostatic radar cross section, the Cubed Sphere sampling scheme required approximately 12% fewer samples compared to that required for traditional sampling while maintaining the same interpolation accuracy over the entire domain. For the bistatic data, it was possible to reduce the number of samples by approximately 35% for high sampling resolutions. Using spline interpolation the number of samples required could be reduced even further.

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“…It has been shown that spline surfaces are a good candidate for continuous RCS models of an aircraft [4], due to their high interpolation accuracy. However, it was also shown that the probability of obtaining a positive RCS interpolation error was about the same as obtaining a negative interpolation error.…”

Section: Introductionmentioning

confidence: 99%

“…However, it was also shown that the probability of obtaining a positive RCS interpolation error was about the same as obtaining a negative interpolation error. Thus, the RCS models presented in [4] are not conservative. The concept of conservative RCS models depends on the objective of the simulation.…”

Section: Introductionmentioning

confidence: 99%

Conservative RCS Models for Tactical Simulation

Persson

Norsell

2015

IEEE Antennas Propag. Mag.

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This paper describes a procedure for generating conservative radar cross section (RCS) models able to meet the computational requirements imposed by simulation and related applications. The key concept is to downsample calculated or measured RCS data retaining local extreme values; thus, a conservative RCS matrix is obtained. Spline approximations are used in order to obtain continuity in the RCS models. RCS models with varying resolution have been generated and analyzed, and it is shown how spatial Fourier transforms can be used when determining feasibility for certain decision making applications. Furthermore, it is found that the interpolation errors obtained from the conservative RCS models are well described by generalized extreme value theory.

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On Modeling RCS of Aircraft for Flight Simulation

Cited by 19 publications

References 11 publications

Review on Computational Electromagnetics

Review on Computational Electromagnetics

Reduction of RCS Samples Using the Cubed Sphere Sampling Scheme

Conservative RCS Models for Tactical Simulation

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