Indoor Mapping with a Mobile Radar Using an EK-PHD Filter
Talvitie, Jukka; Kaltiokallio, Ossi; Rastorgueva-Foi, Elizaveta; Barneto, Carlos Baquero; Keskin, Musa Furkan; Wymeersch, Henk; Valkama, Mikko (2021-09-13)
Talvitie, Jukka
Kaltiokallio, Ossi
Rastorgueva-Foi, Elizaveta
Barneto, Carlos Baquero
Keskin, Musa Furkan
Wymeersch, Henk
Valkama, Mikko
IEEE
13.09.2021
2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202112229512
https://urn.fi/URN:NBN:fi:tuni-202112229512
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [19011]