Spectral Leakage

Introduction The Fast Fourier Transform is one of the most powerful tools in digital signal processing. It allows engineers to inspect the frequency content of signals quickly and efficiently. However, FFT analysis often produces artifacts that can confuse interpretation. One of the most important of these artifacts is spectral leakage. Spectral leakage causes energy from a single tone to spread across multiple frequency bins, making spectra appear broader or more complex than expected. ...

Introduction FFT-based spectral analysis assumes signals are periodic within observation windows. Real signals rarely satisfy this assumption. The result is spectral leakage — energy spreading across frequency bins. Window functions reduce leakage but introduce their own distortions. This article explains how leakage and windowing effects shape real DSP measurements and why engineers must account for them. Why Leakage Occurs When signal periods do not align with FFT window boundaries: discontinuities occur at segment edges frequency content spreads across bins This produces: ...

Introduction Power spectral density estimation using Welch’s method is a standard tool in digital signal processing. It is widely taught, easy to compute, and effective for identifying stationary frequency content. However, engineers frequently encounter confusing behaviors when using Welch PSD for tonal noise detection in real systems: peaks appear and disappear between measurements ripple artifacts resemble narrowband interference drifting tones smear into broadband humps weak interference vanishes under averaging These effects often lead to incorrect notch placement, missed suppression, or unstable filter designs. ...