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Characterization of microstrip antennas using the TLM simulation associated with a Prony‐Pisarenko method
Author(s) -
Dubard J. L.,
Pompei D.,
Le Roux J.,
Papiernik A.
Publication year - 1990
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.1660030407
Subject(s) - microstrip , computer science , antenna (radio) , impulse response , acoustics , microstrip antenna , impulse (physics) , computation , finite difference time domain method , transmission line , electronic engineering , electrical impedance , impedance parameters , algorithm , physics , mathematics , optics , engineering , telecommunications , mathematical analysis , electrical engineering , quantum mechanics
The transmission‐line matrix (TLM) method enables simulation of interior electromagnetic field propagation problems. With the use of absorbent walls, we can simulate exterior problems such as the radiaition of a microstrip antenna. The input impedance is deduced from the standing wave observed in the feedline. The radiation pattern is determined from the field over a plane located in the immediate vicinity of the antenna, using the theory of radiating apertures. However, the CPU time and memory space involved are excessive. Since the radiating structure has several resonant frequencies, it is convenient to apply classical digital signal processing techniques such as finite impulse response filtering associated with a linear prediction method. The present paper focuses on a Prony–Pisarenko method to improve on the TLM method in terms of both computation time and precision of the frequency‐domain analysis of the results. In this case, overall CPU time is reduced by a factor of 2 to 3. The paper discusses the results obtained for radiation patterns. This represents a new field of application for the TLM method whose drawbacks are reduced by using appropriate signal processing methods.