The Problem Solving of System Distortion and Noise Signal Based on FFT

Discrete Fourier Transform (DFT) is a widely used tool for signal analysis and processing in digital signal processing. However, the computation involved in the DFT method makes real-time processing difficult. The Fast Fourier Transform (FFT) algorithm was introduced to overcome this issue by reducing the amount of computation required. This paper discusses the problems leading to FFT system distortion and noise interference, such as insufficient or excessive sampling rates, quantization errors, poor selection of window functions, spectral leakage, and pickup noise. Recent advances in FFT, such as Non-Uniform Discrete Fourier Transform (NDFT), Zoom-FFT, and Chirp-Z transform, are also discussed as potential solutions to these problems. The paper provides a logical analysis of the causes of these problems and introduces methods to address them. The effectiveness of the window function, Zoom-FFT, and anti-aliasing filter is verified and compared. The study of these issues is crucial for the development of digital signal processing in various fields.