A Butterworth filter is a signal processing filter designed to produce a maximally flat frequency response in the passband, meaning it introduces no ripple while attenuating frequencies outside a specified cutoff range. In CSI-based human behavior recognition, it is commonly applied as a low-pass filter to remove high-frequency noise and environmental interference from raw CSI amplitude or phase signals, thereby preserving the relevant motion-induced signal components that correspond to human activities. Key variants include low-pass, high-pass, and band-pass configurations, with filter order serving as an important parameter that controls the steepness of the roll-off between passband and stopband, allowing researchers to tune the trade-off between noise suppression and signal distortion.
Source Papers
- A Survey on Human Behavior Recognition Using Channel State Information ↗ — A Survey on Human Behavior Recognition Using Channel State I
- Channel State Information from Pure Communication to Sense and Track Human Motion: A Survey ↗ — Channel State Information from Pure Communication to Sense a
- Dimensionless numbers reveal distinct regimes in the structure and dynamics of pedestrian crowds ↗ — Dimensionless numbers reveal distinct regimes in the structu