Assessment of Micro-Doppler based road targets recognition based on co-operative multi-sensor automotive radar applications

Tools

Striano, Pasquale and Ilioudis, Christos V. and Clemente, Carmine and Soraghan, John J.; (2020) Assessment of Micro-Doppler based road targets recognition based on co-operative multi-sensor automotive radar applications. In: 2020 IEEE Radar Conference (RadarConf20). IEEE, ITA. ISBN 9781728189437 (https://doi.org/10.1109/RadarConf2043947.2020.9266...)

[thumbnail of Striano-etal-IEEE-RADAR-2020-Assessment-of-micro-doppler-based-road-targets-recognition-based]
Preview
 Text. Filename: Striano_etal_IEEE_RADAR_2020_Assessment_of_micro_doppler_based_road_targets_recognition_based.pdf
Accepted Author Manuscript
Download (886kB)| Preview

Abstract

Radar systems have become one of the principal sensory components in automotive vehicles, due to their ability to detect and discriminate between different objects in various scenarios. In this paper the micro-Doppler signature is used to identify road targets as cyclist, person, group of people, dog walking, and dog trotting. In order to boost the performance of Automatic Target Recognition in automotive environment, each node could share its micro-Doppler based features in a co-operative manner, using novel Vehicle To Vehicle communication frameworks based on joint radar and communication systems. The classification performance is evaluated considering two scenarios, a single-sensor scenarios where the micro-Doppler signature is observed by a single user, and a multi-sensor scenarios where each user shares its feature vector.

ORCID iDs

Striano, Pasquale, Ilioudis, Christos V. ORCID logoORCID: https://orcid.org/0000-0002-7164-6461, Clemente, Carmine ORCID logoORCID: https://orcid.org/0000-0002-6665-693X and Soraghan, John J. ORCID logoORCID: https://orcid.org/0000-0003-4418-7391;
CORE (COnnecting REpositories)