Indoor Mapping with a Mobile Radar Using an EK-PHD Filter
Paper i proceeding, 2021

Integrated communications, localization and sensing is one of the most addressed technologies considered for future mobile communications systems. In this context, a user equipment (UE)-centric mobile radar has been proposed to introduce improved situational awareness, and consequently potential improvement in network performance. In this paper, we derive an extended Kalman probability hypothesis density (EK-PHD) filter with a novel feature model, for a mobile radar based environment mapping, where range-angle detections are used to track map objects over time for dynamic map construction. In order to evaluate the performance of the proposed filtering approach, we employ a realistic ray-tracing-based simulation setup, which models the full transmission chain from the transmitted IQ-samples to mapping results. Besides this, a simplified measurement model considering solely single-bounce specular reflections is exploited for providing further insight into the filter performance. The obtained results show that the proposed EK-PHD filter is able to provide high-quality mapping results, reaching around 10 cm landmark estimation accuracy in the considered millimeter wave simulation setup.

millimeter wave

extended Kalman filter

probability hypothesis density

mobile radar

environmental mapping

Författare

Jukka Talvitie

Tampereen Yliopisto

Ossi Kaltiokallio

Tampereen Yliopisto

Elizaveta Rastorgueva-Foi

Tampereen Yliopisto

Carlos Baquero Barneto

Tampereen Yliopisto

Furkan Keskin

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

M. Valkama

Tampereen Yliopisto

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

Vol. 2021-September

32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
Virtual, Helsinki, Finland,

Ämneskategorier

Annan data- och informationsvetenskap

Kommunikationssystem

Signalbehandling

DOI

10.1109/PIMRC50174.2021.9569630

Mer information

Senast uppdaterat

2021-11-12