Echo-Window Sensitivity of Spectral Features in Ultrasonic Backscatter Characterization of PE and PMMA Microplastics

Abstract

Ultrasonic backscatter provides a non-destructive approach for characterizing microplastic particles; however, the spectral features extracted from an echo can depend on the signal segment selected for analysis. This study investigates the sensitivity of polyethylene (PE) and poly(methyl methacrylate) (PMMA) spectral-feature differences to echo-analysis window length using a publicly available high-frequency ultrasonic backscatter dataset. Signals sharing a common 50-μm size label were analyzed using peak-centered windows of 64, 128, 256, and 384 samples. After mean removal and Hamming tapering, spectral centroid, spectral spread, and normalized spectral entropy were extracted from the Fourier-domain representation. Spatially neighboring measurements were grouped before statistical comparison to reduce the influence of repeated local observations. The results show clear feature-dependent window sensitivity. The PE–PMMA centroid difference remained comparatively stable, changing by only about 3.2% between the shortest and longest windows, whereas the spectral-spread difference increased by approximately

115%. Spectral entropy also showed substantial but non- monotonic variation with window length. These findings

demonstrate that echo-analysis window selection is an important digital signal processing parameter and should be considered when evaluating the robustness and reproducibility of ultrasonic spectral features for microplastic characterization.