A New Framework for the Detection and Removal of Glitches in InSight Seismic Data
- 1School of Engineering The University of Manchester Manchester UK
Abstract
The InSight mission has collected a wealth of valuable seismic data from Mars. Analyses of these recordings have produced important new insights into the planet's interior structure and geological activity. However, the presence of numerous one‐sided transient signals, known as “glitches,” introduces difficulty and complexity into the processing of InSight seismic data. At present, no existing method is capable of perfectly detecting and removing all glitches, owing to their large number and varied origins. This study proposes a new glitch detection and removal approach by introducing a physically interpretable signal‐processing framework based on shock‐waveform decomposition (SWD) method. By exploiting the strong representational capability of the shock‐waveform, the proposed method decomposes raw seismic data into shock‐waveform components and identifies those associated with glitches and high‐frequency spikes for selective removal. Comparative analyses with established glitch detection and removal techniques demonstrate that the SWD‐based method achieves detection performance comparable to existing approaches, with intermediate detection sensitivity between that of the MPS method and those of the UCLA and GlitchNet methods and advantages of mathematical simplicity and a physical interpretation. In addition, the proposed approach effectively removes spikes occurring at glitch onset in the representative comparisons, resulting in cleaner processed signals in these cases.
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BibTeX
@article{lu2026framework,
title = {{A New Framework for the Detection and Removal of Glitches in InSight Seismic Data}},
author = {Andong Lu and Q. M. Li},
journal = {Earth and Space Science},
year = {2026},
month = oct,
doi = {10.1029/2026ea005204},
url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2026EA005204},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - A New Framework for the Detection and Removal of Glitches in InSight Seismic Data
AU - Andong Lu
AU - Q. M. Li
PY - 2026
DA - 2026/10/22
JO - Earth and Space Science
DO - 10.1029/2026ea005204
UR - https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2026EA005204
AB - The InSight mission has collected a wealth of valuable seismic data from Mars. Analyses of these recordings have produced important new insights into the planet's interior structure and geological activity. However, the presence of numerous one‐sided transient signals, known as “glitches,” introduces difficulty and complexity into the processing of InSight seismic data. At present, no existing method is capable of perfectly detecting and removing all glitches, owing to their large number and varied origins. This study proposes a new glitch detection and removal approach by introducing a physically interpretable signal‐processing framework based on shock‐waveform decomposition (SWD) method. By exploiting the strong representational capability of the shock‐waveform, the proposed method decomposes raw seismic data into shock‐waveform components and identifies those associated with glitches and high‐frequency spikes for selective removal. Comparative analyses with established glitch detection and removal techniques demonstrate that the SWD‐based method achieves detection performance comparable to existing approaches, with intermediate detection sensitivity between that of the MPS method and those of the UCLA and GlitchNet methods and advantages of mathematical simplicity and a physical interpretation. In addition, the proposed approach effectively removes spikes occurring at glitch onset in the representative comparisons, resulting in cleaner processed signals in these cases.
SN - 2333-5084
SN - 2333-5084
ER -