Indoor Mapping with a Mobile Radar Using an EK-PHD Filter
Paper in 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.

extended Kalman filter

mobile radar

probability hypothesis density

millimeter wave

environmental mapping

Author

Jukka Talvitie

University of Tampere

Ossi Kaltiokallio

University of Tampere

Elizaveta Rastorgueva-Foi

University of Tampere

Carlos Baquero Barneto

University of Tampere

Furkan Keskin

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Henk Wymeersch

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

M. Valkama

University of Tampere

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

Vol. 2021-September
9781728175867 (ISBN)

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

A New Waveform for Joint Radar and Communications Beyond 5G

European Commission (EC) (EC/H2020/888913), 2020-09-01 -- 2022-08-31.

Subject Categories

Other Computer and Information Science

Communication Systems

Signal Processing

DOI

10.1109/PIMRC50174.2021.9569630

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1/3/2024 9