Gyroscope Noise Analysis Using Allan Variance Algorithm

This article introduces a specialized program designed to analyze gyroscope noise to enhance sensor performance. The core implementation utilizes the Allan variance algorithm, which processes time-series data to characterize various noise components including angle random walk, bias instability, and rate random walk. The algorithm operates by computing the variance of data clusters at different time intervals, enabling detailed identification of noise sources and their properties. Additionally, the program incorporates visualization tools that generate standard Allan deviation plots and noise decomposition charts, helping users intuitively interpret analysis results and make informed calibration decisions. The complete workflow includes data preprocessing, Allan variance calculation, noise parameter extraction, and graphical output generation. Overall, this program serves as a comprehensive tool for understanding and managing gyroscope noise characteristics through both analytical and visual approaches.