P1 - Analysis of Ultrasound Echoes for Object Properties Characterisation
- Event
- iCCC2026 - iCampus Cottbus Conference
2026-05-05 - 2026-05-07
Cottbus - Band
- Poster
- Chapter
- Akustik & Ultraschallsensorik
- Author(s)
- P. Suawa, C. Herglotz - BTU Cottbus-Senftenberg, Cottbus, M. Jongmanns - Fraunhofer IPMS, Dresden
- Pages
- 124 - 127
- DOI
- 10.5162/iCCC2026/P1
- ISBN
- 978-3-910600-10-2
- Price
- free
Abstract
This work analyzes ultrasound echoes across multiple objects using a compact set of physically interpretable time- and frequency-domain features, in addition to the raw waveform structure. Unlike black-box models such as deep neural networks or ensembles, which prioritize accuracy over transparency, our approach emphasizes descriptors with direct physical meaning. We extract features that capture geometry, reflectivity, spectral richness, and structural complexity to provide classifiers with interpretable inputs that explain the physical basis for object recognition. Echoes from five objects were measured across varying orientations and placements. The Time-of-Flight (ToF) decreased near normal incidence and increased at oblique angles, reflecting the propagation geometry. Energy differed by a factor of five between dense-filled and hollow objects, while bandwidth broadened by several hundred hertz under specific orientations. Complementary visualizations using Short-Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT), and Principal Component Analysis (PCA) revealed object-dependent patterns consistent with the scalar features. These results demonstrate that ultrasound echoes encode rich, interpretable information, supporting lightweight featurebased analysis for transparent and low-power embedded sensing.