no code implementations • 29 Feb 2024 • Dingyang Wang, Francesco Fioranelli, Alexander Yarovoy
In this paper, the problem of formulating effective processing pipelines for indoor human tracking is investigated, with the usage of a Multiple Input Multiple Output (MIMO) Frequency Modulated Continuous Wave (FMCW) radar.
no code implementations • 20 Feb 2024 • Sen Yuan, Francesco Fioranelli, Alexander Yarovoy
The problem of 3D high-resolution imaging in automotive multiple-input multiple-output (MIMO) side-looking radar using a 1D array is considered.
no code implementations • 20 Feb 2024 • Ignacio Roldan, Andras Palffy, Julian F. P. Kooij, Dariu M. Gavrila, Francesco Fioranelli, Alexander Yarovoy
In this paper, we address the limitations of traditional constant false alarm rate (CFAR) target detectors in automotive radars, particularly in complex urban environments with multiple objects that appear as extended targets.
no code implementations • 24 Jan 2023 • Ignacio Roldan, Francesco Fioranelli, Alexander Yarovoy
Data from a high angular resolution radar, i. e., a radar with a large antenna aperture, is used to train a deep neural network to extrapolate the antenna element's response.
1 code implementation • IEEE Radar Conference 2021 • Daniel Gusland, Jonas M. Christiansen, Børge Torvik, Francesco Fioranelli, Sevgi Z. Gurbuz, Matthew Ritchie
In this paper, we discuss an "open radar initiative" aimed at promoting the sharing of radar datasets and a common framework for acquiring data.
no code implementations • 2 Dec 2019 • Alex Turpin, Gabriella Musarra, Valentin Kapitany, Francesco Tonolini, Ashley Lyons, Ilya Starshynov, Federica Villa, Enrico Conca, Francesco Fioranelli, Roderick Murray-Smith, Daniele Faccio
Traditional paradigms for imaging rely on the use of a spatial structure, either in the detector (pixels arrays) or in the illumination (patterned light).