000163713 001__ 163713
000163713 005__ 20251030150826.0
000163713 0247_ $$2doi$$a10.3390/electronics14193755
000163713 0248_ $$2sideral$$a145786
000163713 037__ $$aART-2025-145786
000163713 041__ $$aeng
000163713 100__ $$aLabodía, Miguel
000163713 245__ $$aRadiation Pattern Recovery from Tilted Orbital Sampling Measurements via Sparse Spherical Harmonic Expansion
000163713 260__ $$c2025
000163713 5060_ $$aAccess copy available to the general public$$fUnrestricted
000163713 5203_ $$aThis paper proposes a reconstruction framework for estimating the far-field (FF) radiation patterns of large, heavy, or non-rotatable wireless-enabled systems. The method combines a tilted orbital sampling (ToS) strategy with sparse spherical harmonic (SH) expansion, compressed sensing (CS), and convex optimization (CO), thereby linking a mechanically constrained acquisition scheme with a mathematically efficient recovery process. The purpose of this integration is not only to reduce the number of measurements but also to retrieve the radiation information most relevant to Internet of Things (IoT) devices and bulky equipment that cannot be easily rotated within anechoic chambers. The framework is validated on two representative cases: a canonical half-wave dipole and a commercial Wi-Fi-enabled device. In the latter and more challenging case, accurate reconstruction is achieved with fewer than 30 SH coefficients and using less than 20% of the measurements required by a conventional full-sphere scan, with the normalized root-mean-square error remaining below 5%. Although inaccessible angular regions may be partially uncharacterized, such directions are of minor relevance for the intended operational coverage. The resulting SH-based representation can be seamlessly integrated into ray-tracing propagation simulators and electromagnetic optimization workflows, enabling efficient and application-oriented OTA characterization under realistic chamber constraints.
000163713 536__ $$9info:eu-repo/grantAgreement/EUR/AEI/CPP2021-008938$$9info:eu-repo/grantAgreement/EUR/AEI/TED2021-129274B-I00$$9info:eu-repo/grantAgreement/ES/ISCIII/PI21-00440$$9info:eu-repo/grantAgreement/ES/MICINN-AEI-FEDER/PID2019-103939RB-I00
000163713 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttps://creativecommons.org/licenses/by/4.0/deed.es
000163713 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000163713 700__ $$0(orcid)0000-0002-4099-9918$$aMediano, Arturo$$uUniversidad de Zaragoza
000163713 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica
000163713 773__ $$g14, 19 (2025), 3755 [22 pp.]$$pElectronics (Basel)$$tElectronics (Basel)$$x2079-9292
000163713 8564_ $$s2876809$$uhttps://zaguan.unizar.es/record/163713/files/texto_completo.pdf$$yVersión publicada
000163713 8564_ $$s2561722$$uhttps://zaguan.unizar.es/record/163713/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000163713 909CO $$ooai:zaguan.unizar.es:163713$$particulos$$pdriver
000163713 951__ $$a2025-10-30-14:39:31
000163713 980__ $$aARTICLE