The simultaneous interpolation of antenna radiation patterns in both the spatial and frequency domains using model-based parameter estimation

Citation
Dh. Werner et Rj. Allard, The simultaneous interpolation of antenna radiation patterns in both the spatial and frequency domains using model-based parameter estimation, IEEE ANTENN, 48(3), 2000, pp. 383-392
Citations number
18
Categorie Soggetti
Information Tecnology & Communication Systems
Journal title
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
ISSN journal
0018926X → ACNP
Volume
48
Issue
3
Year of publication
2000
Pages
383 - 392
Database
ISI
SICI code
0018-926X(200003)48:3<383:TSIOAR>2.0.ZU;2-9
Abstract
The Pade rational function fitting model commonly used for model-based para meter estimation (MBPE) in the frequency domain is enhanced to include spat ial dependence in the numerator and denominator coefficients. This allow's the function to interpolate an antenna radiated electric field pattern in b oth the frequency and spatial domains simultaneously, such that a single se t of coefficients ran be used to accurately reconstruct an entire radiation pattern at any frequency in the fitting-model range. A simple procedure is introduced for transforming interpolated electric fields into gain pattern s using input impedance versus frequency curves also obtained via MBPE. The utility of this method is demonstrated by applying it to a dipole antenna over a frequency range of 150-950 MHz and using a polynomial representation in theta for the coefficient spatial dependence. It is also used to estima te radiation patterns for a three-element Yagi array between the frequencie s of 470 and 500 MHz using a binomial representation for the spatial variat ion that includes terms dependent on theta as well as phi. The use of this method for interpolating radiation patterns has at least two significant ad vantages; one being large compression ratios for the amount of data that mu st be stored to accurately reproduce patterns and the other being a signifi cant decrease in the amount of time required for modeling problems with lar ge computational domains.