Grouping Strategies of Discrete Elements for Efficient Power Pattern Tolerance Analysis of Antennas/Radomes Using Monte Carlo Method

Abstract

This work presents a simple grouping method for efficient power pattern tolerance analysis of antennas/radomes using the Monte Carlo method. The discrete elements, as antenna array elements or antenna/radome discretized meshes, are grouped into a limited number of clusters to reduce the number of independent random variables. Three grouping strategies based on Cartesian coordinates, polar coordinates, and random case are presented to group the discrete elements into eight types. A method combining two sets of results with pattern main-lobe-region and sidelobe-region optimal grouping numbers is proposed to improve the tolerance analysis precision. A 60 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times $ </tex-math></inline-formula> 60 uniformly excited rectangular array antenna with excitation errors and its variants with amplitude taper or circular aperture, and a spherical radome with more than 1100 discrete meshes are considered. The results show that the proposed method can yield desirable electromagnetic (EM) performance variation ranges using 103–2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times \,\,10^{3}$ </tex-math></inline-formula> random samplings. Through grouping, the obtained EM performance interval percentages with respect to the interval analysis results are improved from 3%–6% to 47%–88% for the antenna cases and from 1%–2% to 19%–30% for the radome cases, respectively.