This paper presents an approach to analyze experimental data contaminated with noise from Anthropomorphic Test Devices (ATDs). This approach is based on information extraction procedures and they are illustrated through an analysis of Hybrid III 3-year-old and Q3 ATDs test data.
The methodology used for extracting information and ATD test data analysis includes optimized filtering, spectral coherence, auto- and crosscorrelation analysis, and Kalman filtering. This work investigates promising techniques of extracting information from noisy ATD signals that are not commonly used in the automotive industry.