Известия высших учебных заведений России: Радиоэлектроника (Apr 2022)

Analytical Approach to Designing a Combined-Mode Resonator Filter on Surface Acoustic Waves Using the Model of Coupling of Modes

  • A. S. Koigerov

DOI
https://doi.org/10.32603/1993-8985-2022-25-2-16-28
Journal volume & issue
Vol. 25, no. 2
pp. 16 – 28

Abstract

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Introduction. Bandpass filters are important components that determine the basic characteristics of transmitting and receiving radio electronic equipment. Such filters implemented on surface acoustic waves (SAW) not only demonstrate excellent electrical parameters, but also meet compactness requirements. The relevant research task of reducing the design time and optimizing the filter’s cost can be solved by either using modern computational software or improving existing modeling tools.Aim. To describe the current state and main features of approaches to calculating SAW-based bandpass filters using the model of coupled modes and its formalization based on P-matrices. To describe the main principles and approaches on the example of designing a combined-mode resonator filter on leaky SAW and comparing the calculated and experimental data.Materials and methods. A theoretical study was carried out using the mathematical theory of differential equations presented in a matrix form, as well as the methods of finite element analysis and circuit theory. The results were processed in MatLab and COMSOL.Results. The current state of the analytical approach to designing SAW-based filters using the model of coupled modes and its formalization based on P-matrices was described. An original design for a resonator filter based on leaky SAW at 49° YX-cut of lithium niobate was proposed. The filter has a relative bandwidth of 5.8 %, an insertion loss of –3.7 dB, and a stop-band rejection of –50 dB. A technique for calculating SAW-based filters was proposed.Conclusion. The proposed analytical approach to designing SAW-based bandpass filters allows the filter characteristics (e.g., transmission factor) to be reliably predicted at the modeling stage, thereby reducing the number of experimental iterations and increasing the development efficiency.

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