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SIE-Based Substructure Characteristic Mode Analysis on Stacked Dielectric Resonator Antennas | IEEE Conference Publication | IEEE Xplore

SIE-Based Substructure Characteristic Mode Analysis on Stacked Dielectric Resonator Antennas


Abstract:

The recently proposed surface integral equation-based substructure characteristic mode analysis (SIE-SCMA) is applied on a stacked dielectric resonator antenna (SDRA) con...Show More

Abstract:

The recently proposed surface integral equation-based substructure characteristic mode analysis (SIE-SCMA) is applied on a stacked dielectric resonator antenna (SDRA) containing two materials for the first time. By treating the finite ground plane (GP) as passive loading, the novel characteristic mode (CM) solver better identifies the resonance of the combined dielectric block, and then returns a reasonable modal significance (MS) spectrum coinciding with the classic DRA theory. Unlike the traditional full-structure SIE-CMA, the SIE-SCAM provides informative resonant frequency, modal linewidth, and modal radiation pattern.
Date of Conference: 15-17 November 2021
Date Added to IEEE Xplore: 23 December 2021
ISBN Information:
Conference Location: Chongqing, China

I. Introduction

Surface integral equation-based characteristic mode analysis (SIE-CMA) draws increasing in antenna design as it reveals the intrinsic nature of a radiating or scattering structure effectively and efficiently [1], [2]. Nevertheless, for dielectric-based antennas, though the well-known plight caused by spurious modes has been conquered [3], SIE-CMA is hardly applied. Widely applied commercial SIE-CMA solvers are either unable to handle dielectric structures or ineffective in identifying characteristic modes of the main dielectric object in complex circumstances [4]. For instance, even for the simplest case, i.e. a dielectric resonator antenna (DRA) on a finite ground plane (GP), common SIE-CMA cannot accurately extract the CM unless the GP is assumed infinitely large [5]. Metallic antennas also suffer more or less from the similar problem [6].

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