Anomaly Distinguishability in an Asteroid Analogue Using Quasi-Monostatic Experimental Radar Measurements

This study conducts a quantitative distinguishability analysis using quasi-monostatic experimental radar data to find a topographic and backpropagated tomographic reconstruction for an analogue of asteroid Itokawa (25143). In particular, we consider a combination of travel-time and wavefield backpropagation tomography using the time-frequency representation (TFR) and principal component analysis (PCA) approaches as filtering techniques. Furthermore, we hypothesise that the travel time of the main peaks in the signal can be projected as a topographic imaging of the analogue asteroid while also presenting a tomographic reconstruction based on the main peaks in the signal. We compare the performance of several different filtering approaches covering several noise levels and two hypothetical interior structures: homogeneous and detailed. Our results suggest that wavefield information is vital for obtaining an appropriate reconstruction quality regardless of the noise level and that different filters affect the distinguishability under different assumptions of the noise. The results also suggest that the main peaks of the measured signal can be used to topographically distinguish the signatures in the measurements, hence the interior structure of the different analogue asteroids. Similarly, a tomographic reconstruction with the main peaks of the measured signal can be used to distinguish the interior structure of the different analogue asteroids.

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Publication Details

Journal
IEEE Transactions on Computational Imaging
Published
2025-01-01
DOI
https://doi.org/10.1109/tci.2025.3597429
Primary Topic
Astro and Planetary Science
Type
article
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article

Anomaly Distinguishability in an Asteroid Analogue Using Quasi-Monostatic Experimental Radar Measurements

Astrid Dufaure, Liisa-Ida Sorsa, Alain Hèrique, Yusuf Oluwatoki Yusuf et al.
IEEE Transactions on Computational Imaging
Astro and Planetary Science
article

Anomaly Distinguishability in an Asteroid Analogue Using Quasi-Monostatic Experimental Radar Measurements

Astrid Dufaure, Liisa-Ida Sorsa, Alain Hèrique, Yusuf Oluwatoki Yusuf, Sampsa Pursiainen, Jean‐Michel Geffrin, Christelle Eyraud
article en

Abstract

This study conducts a quantitative distinguishability analysis using quasi-monostatic experimental radar data to find a topographic and backpropagated tomographic reconstruction for an analogue of asteroid Itokawa (25143). In particular, we consider a combination of travel-time and wavefield backpropagation tomography using the time-frequency representation (TFR) and principal component analysis (PCA) approaches as filtering techniques. Furthermore, we hypothesise that the travel time of the main peaks in the signal can be projected as a topographic imaging of the analogue asteroid while also presenting a tomographic reconstruction based on the main peaks in the signal. We compare the performance of several different filtering approaches covering several noise levels and two hypothetical interior structures: homogeneous and detailed. Our results suggest that wavefield information is vital for obtaining an appropriate reconstruction quality regardless of the noise level and that different filters affect the distinguishability under different assumptions of the noise. The results also suggest that the main peaks of the measured signal can be used to topographically distinguish the signatures in the measurements, hence the interior structure of the different analogue asteroids. Similarly, a tomographic reconstruction with the main peaks of the measured signal can be used to distinguish the interior structure of the different analogue asteroids.

IEEE Transactions on Computational ImagingVol. 11
Centre National de la Recherche Scientifique (FR), Tampere University of Applied Sciences (FI), Tampere University (FI), Institut Fresnel (FR), Tampere University (FI), Centrale Méditerranée (FR), Université Grenoble Alpes (FR)
Climate action
Openalex Percentile: Top 85%
Astro and Planetary Science
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