Spectrum Analysis with the Prime Factor Algorithm on Embedded Systems

TL;DR

This paper presents the development of a fast Fourier transform using the prime factor algorithm tailored for embedded systems, enabling efficient spectral analysis in real-time applications like communication and signal processing.

Contribution

It introduces a novel implementation of the prime factor algorithm for FFT on a specific embedded platform, optimizing spectral analysis performance.

Findings

Achieved efficient 36-point DFT computation on Nuvoton Nu-LB-NUC140V2

Demonstrated improved speed for real-time spectral analysis

Validated the algorithm's effectiveness in embedded environments

Abstract

This paper details the purpose, difficulties, theory, implementation, and results of developing a Fast Fourier Transform (FFT) using the prime factor algorithm on an embedded system. Many applications analyze the frequency content of signals, which is referred to as spectral analysis. Some of these applications include communication systems, radar systems, control systems, seismology, speech, music, sonar, finance, image processing, and neural networks. For many real-time applications, the speed at which the spectral analysis is performed is crucial. In order to perform spectral analysis, a Fourier transform is employed. For embedded systems, where spectral analysis is done digitally, a discrete Fourier transform (DFT) is employed. The main goal for this project is to develop an FFT for a 36-point DFT on the Nuvoton Nu-LB-NUC140V2. In this case, the prime factor algorithm is utilized to compute a fast DFT.