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Surrogate‐assisted tolerance analysis of low‐sidelobe linear arrays with microstrip corporate feeds
Author(s) -
Koziel Slawomir,
Ogurtsov Stanislav
Publication year - 2018
Publication title -
international journal of numerical modelling: electronic networks, devices and fields
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.249
H-Index - 30
eISSN - 1099-1204
pISSN - 0894-3370
DOI - 10.1002/jnm.2533
Subject(s) - microstrip , computer science , surrogate model , electronic engineering , tolerance analysis , fidelity , high fidelity , algorithm , acoustics , engineering , physics , telecommunications , machine learning , engineering drawing
Abstract This paper addresses the problem of fast statistical analysis of low‐sidelobe linear arrays with microstrip corporate feeds using surrogate‐assisted methods. Tolerances normally lead to a degradation of array performance with respect to circuit and radiation pattern characteristics. Tolerances may be pertinent to array elements, spacing, feed dimensions, and microstrip substrate parameters. Sidelobe level (SLL) is affected by these parameter deviations in case of low sidelobe designs. Accurate evaluation of an SLL requires full‐wave electromagnetic (EM) simulations, which can be very computationally expensive. Consequently, performing statistical analysis directly at the level of the EM model of the array is impractical. Here, we discuss techniques that permits fast tolerance analysis yet at the high‐fidelity level of EM modeling. These include various surrogate modeling and correction techniques that are used to align the fast surrogates with the respective EM models.