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Different Metrics for Singular Value Optimization in Near-Field Antenna Characterization

Amedeo Capozzoli, Claudio Curcio, Angelo Liseno

2021Sensors18 citationsDOIOpen Access PDF

Abstract

We deal with the use of different metrics in the framework of the Singular Value Optimization (SVO) technique for near-field antenna characterization. SVO extracts the maximum amount of information on an electromagnetic field over a certain domain from field samples on an acquisition domain, with a priori information on the source, e.g., support information. It determines the field sample positions by optimizing a functional featuring the singular value dynamics of the radiation operator and representing a measure of the information collected by the field samples. Here, we discuss in detail and compare the use, in the framework of SVO, of different objective functionals and so of different information measures: Shannon number, mutual information, and Fisher information. The numerical results show that they yield a similar performance.

Topics & Concepts

A priori and a posterioriField (mathematics)Singular valueMeasure (data warehouse)Mutual informationComputer scienceAntenna (radio)Characterization (materials science)Sample (material)Domain (mathematical analysis)Operator (biology)MathematicsData miningArtificial intelligenceOpticsTelecommunicationsMathematical analysisPhysicsEpistemologyTranscription factorChemistryGeneBiochemistryRepressorPhilosophyThermodynamicsPure mathematicsEigenvalues and eigenvectorsQuantum mechanicsElectromagnetic Compatibility and MeasurementsMicrowave and Dielectric Measurement TechniquesAntenna Design and Optimization