Communication publiée dans un ouvrage (Colloques, congrès, conférences scientifiques et actes)
Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
Mishra, K. V.; R., B. Shankar M.; OTTERSTEN, Björn
2020 • In 2020 IEEE Radar Conference (RadarConf20), Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
[en] As the use of radars in autonomous driving systems becomes more prevalent, these systems are increasingly susceptible to mutual interference. In this paper, we employ stochastic geometry to model the automotive radar interference in realistic traffic scenarios and then derive trade-offs between the radar design parameters and detection probability. Prior works model the locations of radars in the lane as a homogeneous Poisson point process (PPP). However, the PPP models assume all nodes to be independent, do not account for the lengths of vehicles, and ignore spatial mutual exclusion. In order to provide a more realistic interference effect, we adopt the Matérn hardcore process (MHCP) instead of PPP, in which two vehicles are not closer than an exclusion radius from one another. We show that the MHCP model leads to more practical design trade-offs for adapting the radar parameters than the conventional PPP model.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Mishra, K. V.
R., B. Shankar M.
OTTERSTEN, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
Date de publication/diffusion :
04 décembre 2020
Nom de la manifestation :
Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
Lieu de la manifestation :
Florence, Italie
Date de la manifestation :
from 21-09-20 to 25-09-20
Titre de l'ouvrage principal :
2020 IEEE Radar Conference (RadarConf20), Stochastic-Geometry-Based Interference Modeling in Automotive Radars Using Matérn Hard-Core Process
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