[en] This paper shows the enhancement in detection performance in an automotive scenario by leveraging the backscattered communication signals from vehicles at the target scene. A sensor fusion algorithm is proposed to benefit from the information from radar and communication to improve the final range estimates. We demonstrate theoretically and illustrate through simulation that our proposed scheme enhances the radar detection performance. Thus the proposed scheme offers a solution for augmenting existing sensing capabilities to enhance detecting capabilities in a dynamic automotive scenario.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
DOKHANCHI, Sayed Hossein ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SigCom
MYSORE RAMA RAO, Bhavani Shankar ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SPARC
Mishra, Kumar Vijay
OTTERSTEN, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Enhanced Automotive Target Detection through Radar and Communications Sensor Fusion
Date de publication/diffusion :
13 mai 2021
Nom de la manifestation :
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Lieu de la manifestation :
Toronto, Canada
Date de la manifestation :
6-06-2021 to 11-06-2021
Sur invitation :
Oui
Manifestation à portée :
International
Titre de l'ouvrage principal :
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)