000119017 001__ 119017
000119017 005__ 20221020151542.0
000119017 0247_ $$2doi$$a10.3390/s20195686
000119017 0248_ $$2sideral$$a130231
000119017 037__ $$aART-2020-130231
000119017 041__ $$aeng
000119017 100__ $$aVermiglio, Simona
000119017 245__ $$aParametric electromagnetic analysis of radar-based advanced driver assistant systems
000119017 260__ $$c2020
000119017 5060_ $$aAccess copy available to the general public$$fUnrestricted
000119017 5203_ $$aEfficient and optimal design of radar-based Advanced Driver Assistant Systems (ADAS) needs the evaluation of many different electromagnetic solutions for evaluating the impact of the radome on the electromagnetic wave propagation. Because of the very high frequency at which these devices operate, with the associated extremely small wavelength, very fine meshes are needed to accurately discretize the electromagnetic equations. Thus, the computational cost of each numerical solution for a given choice of the design or operation parameters, is high (CPU time consuming and needing significant computational resources) compromising the efficiency of standard optimization algorithms. In order to alleviate the just referred difficulties the present paper proposes an approach based on the use of reduced order modeling, in particular the construction of a parametric solution by employing a non-intrusive formulation of the Proper Generalized Decomposition, combined with a powerful phase-angle unwrapping strategy for accurately addressing the electric and magnetic fields interpolation, contributing to improve the design, the calibration and the operational use of those systems.
000119017 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000119017 590__ $$a3.576$$b2020
000119017 591__ $$aINSTRUMENTS & INSTRUMENTATION$$b14 / 64 = 0.219$$c2020$$dQ1$$eT1
000119017 591__ $$aCHEMISTRY, ANALYTICAL$$b26 / 83 = 0.313$$c2020$$dQ2$$eT1
000119017 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b82 / 273 = 0.3$$c2020$$dQ2$$eT1
000119017 592__ $$a0.636$$b2020
000119017 593__ $$aAnalytical Chemistry$$c2020$$dQ2
000119017 593__ $$aAtomic and Molecular Physics, and Optics$$c2020$$dQ2
000119017 593__ $$aBiochemistry$$c2020$$dQ2
000119017 593__ $$aMedicine (miscellaneous)$$c2020$$dQ2
000119017 593__ $$aInformation Systems$$c2020$$dQ2
000119017 593__ $$aInstrumentation$$c2020$$dQ2
000119017 593__ $$aElectrical and Electronic Engineering$$c2020$$dQ2
000119017 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000119017 700__ $$aChampaney, Victor
000119017 700__ $$aSancarlos, Abel
000119017 700__ $$aDaim, Fatima
000119017 700__ $$aKedzia, Jean Claude
000119017 700__ $$aDuval, Jean Louis
000119017 700__ $$aDiez, Pedro
000119017 700__ $$aChinesta, Francisco
000119017 773__ $$g20, 19 (2020), 5686 [15 pp.]$$pSensors$$tSensors$$x1424-8220
000119017 8564_ $$s862749$$uhttps://zaguan.unizar.es/record/119017/files/texto_completo.pdf$$yVersión publicada
000119017 8564_ $$s2335202$$uhttps://zaguan.unizar.es/record/119017/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000119017 909CO $$ooai:zaguan.unizar.es:119017$$particulos$$pdriver
000119017 951__ $$a2022-10-20-09:19:38
000119017 980__ $$aARTICLE