A novel ultrasonic wave-based analog Fourier transform computing system

Uy, Robert Frederik Diaz; Bui, Viet Phuong

doi:10.1063/5.0107621

Cited by 1 publication

(1 citation statement)

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“…To date, the ultrasonic WFC has been investigated only for the FFT of 2D data for image processing, however, 1-D FFT for signal processing is important and how to use such a WFC system for signal processing remains unknown. On the other hand, the WFC system using GHz ultrasonic waves 11 , 13 , 14 passing through a flat lens 15 , 16 will be finally packaged into a chip by semiconductor technologies. Before fabrication and measurement, it is important to validate the idea, investigate the main factors that which cause errors, and optimize the system design.…”

Section: Introductionmentioning

confidence: 99%

Simulation of GHz ultrasonic wave piezoelectric instrumentation for Fourier transform computation

Yang,

Tan,

Bui

et al. 2023

Sci Rep

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The recent emerging alternative to classic numerical Fast Fourier transform (FFT) computation, based on GHz ultrasonic waves generated from and detected by piezoelectric transducers for wavefront computing (WFC), is more efficient and energy-saving. In this paper, we present comprehensive studies on the modeling and simulation methods for ultrasonic WFC computation. We validate the design of the WFC system using ray-tracing, Fresnel diffraction (FD), and the full-wave finite element method (FEM). To effectively simulate the WFC system for inputs of 1-D signals and 2-D images, we verified the design parameters and focal length of an ideal plano-concave lens using the ray-tracing method. We also compared the analytical FFT solution with our Fourier transform (FT) results from 3-D and 2-D FD and novel 2-D full wave FEM simulations of a multi-level Fresnel lens with 1-D signals and 2-D images as inputs. Unlike the previously reported WFC system which catered only for 2-D images, our proposed method also can solve the 1-D FFT effectively. We validate our proposed 2-D full wave FEM simulation method by comparing our results with the theoretical FFT and Fresnel diffraction method. The FFT results from FD and FEM agree well with the digitally computed FFT, with computational complexity reduced from $$O(N^2 logN)$$ O ( N 2 l o g N ) to O(N) for 2-D FFT, and from O(NlogN) to O(N) for 1-D FFT with a large number of signal sampling points N.

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Section: Introductionmentioning

confidence: 99%