Exploring Seismic Signal Detection and Source Identification of Atmospheric Entries: The Hayabusa2 Sample Return Capsule as a Benchmark

This exploratory study investigates whether seismic signals can be used to infer fragmentation during a fireball event. Re-entry objects, particularly sample return capsules (SRCs) such as the one from the Hayabusa2 mission, behave similarly to slow meteors during atmospheric entry and provide valuable insights into natural fireball events. In this study, we initially analyse seismic signals from the Hayabusa2 SRC re-entry, which took place on December 5, 2020, over South Australia. The SRC's signature was captured by a dense network of seismic stations (Eakin, 2018; O'Donnell et al., 2020), offering a unique opportunity to investigate the signals' characteristics and verify their connection to the re-entry event. The ballistic trajectory was confirmed as the source shock mechanism for this event. We isolate this signal and use it as a reference for a ballistic shock signature and compare it to three other fireball case studies, including a suborbital re-entry and two natural meteoroids. Although factors such as local geology and atmospheric conditions were not considered in this preliminary study, our results show promise, with high correlations for events with purely ballistic trajectories and lower correlations for those involving fragmentation or airbursts. This implies that seismic data may be able to disambiguate whether any particular fireball event underwent significant fragmentation or airburst, key phenomena for assessing body strengths.

Publication Details

Journal
ArXiv.org
Published
2025-05-21
Primary Topic
Indian Economic and Social Development
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Exploring Seismic Signal Detection and Source Identification of Atmospheric Entries: The Hayabusa2 Sample Return Capsule as a Benchmark

ArXiv.org
Indian Economic and Social Development
article

Exploring Seismic Signal Detection and Source Identification of Atmospheric Entries: The Hayabusa2 Sample Return Capsule as a Benchmark

article en

Abstract

This exploratory study investigates whether seismic signals can be used to infer fragmentation during a fireball event. Re-entry objects, particularly sample return capsules (SRCs) such as the one from the Hayabusa2 mission, behave similarly to slow meteors during atmospheric entry and provide valuable insights into natural fireball events. In this study, we initially analyse seismic signals from the Hayabusa2 SRC re-entry, which took place on December 5, 2020, over South Australia. The SRC's signature was captured by a dense network of seismic stations (Eakin, 2018; O'Donnell et al., 2020), offering a unique opportunity to investigate the signals' characteristics and verify their connection to the re-entry event. The ballistic trajectory was confirmed as the source shock mechanism for this event. We isolate this signal and use it as a reference for a ballistic shock signature and compare it to three other fireball case studies, including a suborbital re-entry and two natural meteoroids. Although factors such as local geology and atmospheric conditions were not considered in this preliminary study, our results show promise, with high correlations for events with purely ballistic trajectories and lower correlations for those involving fragmentation or airbursts. This implies that seismic data may be able to disambiguate whether any particular fireball event underwent significant fragmentation or airburst, key phenomena for assessing body strengths.

ArXiv.org
Openalex Percentile: Top 40%
Indian Economic and Social Development
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.