@inproceedings{99132f4474e747d390d3297c0979d800,
title = "Spatial-Radon and Doppler Aggregated Radar Odometry",
abstract = "In this paper, a radar-only 2D odometry estimation algorithm is presented. The algorithm stands out by proposing a statistically robust method for aggregating two sources of rotation estimation obtained using radar generated images. The proposed idea was evaluated using real-world data collected with a radar mounted on a mobile robot. When compared to two other alternative algorithms, the proposed method achieved an improvement in the average absolute relative pose error of up to 30.2% and 45% in the translation and rotation part respectively.",
keywords = "Doppler, motion estimation, radar odometry, Radon transform",
author = "Lubanco, {Daniel Louback S.} and Ahmed Hashem and Markus Pichler-Scheder and Thomas Schlechter and Reinhard Feger and Andreas Stelzer",
note = "Publisher Copyright: {\textcopyright} 2024 European Microwave Association (EuMA).; 21st European Radar Conference, EuRAD 2024 ; Conference date: 25-09-2024 Through 27-09-2024",
year = "2024",
doi = "10.23919/EuRAD61604.2024.10734937",
language = "English",
series = "2024 21st European Radar Conference, EuRAD 2024",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "344--347",
booktitle = "21st European Radar Conference, EuRAD 2024",
address = "United States",
}