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Indoor Mapping with...
Indoor Mapping with a Mobile Radar Using an EK-PHD Filter
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- Talvitie, Jukka (författare)
- Tampereen Yliopisto,University of Tampere
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- Kaltiokallio, Ossi (författare)
- Tampereen Yliopisto,University of Tampere
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- Rastorgueva-Foi, Elizaveta (författare)
- Tampereen Yliopisto,University of Tampere
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- Barneto, Carlos Baquero (författare)
- Tampereen Yliopisto,University of Tampere
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- Keskin, Furkan, 1988 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Wymeersch, Henk, 1976 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Valkama, M. (författare)
- Tampereen Yliopisto,University of Tampere
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(creator_code:org_t)
- 2021
- 2021
- Engelska.
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Ingår i: IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC. ; 2021-September
- Relaterad länk:
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https://research.cha... (primary) (free)
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- 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.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Annan data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Other Computer and Information Science (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Kommunikationssystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Communication Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)
Nyckelord
- extended Kalman filter
- mobile radar
- probability hypothesis density
- millimeter wave
- environmental mapping
Publikations- och innehållstyp
- kon (ämneskategori)
- ref (ämneskategori)