computational sensing; handheld SAR; ego-motion; millimeter-wave; deep learning
Abstract :
[en] Affordable millimeter-wave (mmWave) devices enabled radar-based computational sensing systems to be used as the primary modality in a wide range of applications
from vital sign monitoring to surveillance. Such low-power and lightweight mmWave sensors have recently surged the development of portable handheld radar imaging systems operating using synthetic aperture radar (SAR) principles. These systems, however, are commonly coupled with external positioning devices which introduces hardware complexity, cost, and weight. Nonetheless, to the best of our knowledge, solely radar-based ego-motion estimation methods, common to automotive literature, have not been applied to handheld SAR imaging. In this paper, we aim to achieve ego-motion estimation for handheld SAR imaging using a compact sensor equipped with only 3 receiving antennas. Our work highlights the potential of this technique and addresses the limitations that arise by introducing a first prototype deep learning-based approach.
Research center :
Interdisciplinary Centre for Security, Reliability and Trust (SnT) > SPARC- Signal Processing Applications in Radar and Communications
ORAL, Okyanus ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
MURTADA, Ahmed Abdelnaser Elsayed ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust > SPARC > Team Bhavani Shankar MYSORE RAMA RAO
FEUILLEN, Thomas ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
MYSORE RAMA RAO, Bhavani Shankar ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
External co-authors :
no
Language :
English
Title :
Handheld SAR with Learning-Based Ego-Motion Estimation Using a Compact mmWave Sensor
Publication date :
24 September 2025
Event name :
2025 22nd European Radar Conference (EuRAD)
Event organizer :
Institute of Electrical and Electronics Engineers (IEEE)
Event place :
Utrecht, Netherlands
Event date :
from 24 to 26 September 2025
Audience :
International
Main work title :
2025 22nd European Radar Conference (EuRAD)
Publisher :
Institute of Electrical and Electronics Engineers (IEEE)
FNR17391632 - METSA - Metacognitive Radar For Emerging Sensing Applications, 2022 (01/09/2023-31/08/2026) - Bjorn Ottersten FNR18158802 - SURF - Sensing Via Unlimited-sampling For Radio-frequency, 2023 (01/01/2024-30/06/2026) - Thomas Feuillen
Funders :
FNR - Luxembourg National Research Fund
Funding text :
The work is supported by the Luxembourg National Research Fund (FNR) through the CORE project METSA
under grant C22/IS/17391632. TF’s work is supported by FNR CORE SURF Project, ref C23/IS/18158802/SURF.
Commentary :
The experiments presented in this paper were carried out using the HPC facilities of the University of Luxembourg - see https://hpc.uni.lu
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