A Dataset on Human Activity Recognition with a Multistatic Radar Network

Fröhlich AC, Ullmann I (2025)

Publication Type: Conference contribution

Publication year: 2025

Publisher: IEEE

City/Town: New York City

Pages Range: 119-122

Conference Proceedings Title: 2025 22nd European Radar Conference (EuRAD)

Event location: Utrecht NL

DOI: 10.23919/EuRAD65285.2025.11234067

Abstract

The combination of human activity recognition (HAR) with machine learning (ML) has been the subject of extensive research interest in recent years for a number of reasons. A significant amount of academic institutions worldwide are engaged in research activities within this field. However, only a limited number of publications consider the utilisation of networks and a multistatic radar setup. Furthermore, an even smaller number of researchers make the data acquired in their measurement campaigns publicly available. This paper presents a dataset on HAR acquired with a millimeter-wave multistatic radar network. The radars were positioned orthogonally to one another. This configuration allows for the direction-independent acquisition of Doppler data. Additionally, to our best knowledge, our dataset is the first publicly available dataset that provides azimuth information along with range and Doppler. The configuration allowed for the acquisition of direction-independent data. The objective of this paper is to make the acquired data accessible for researchers, with the measurement setup, sensor technology and subjects described, and the data and access information provided.

Authors with CRIS profile

Ann-Christine Fröhlich Lehrstuhl für Hochfrequenztechnik (LHFT) Ingrid Ullmann Lehrstuhl für Hochfrequenztechnik (LHFT)

How to cite

APA:

Fröhlich, A.-C., & Ullmann, I. (2025). A Dataset on Human Activity Recognition with a Multistatic Radar Network. In 2025 22nd European Radar Conference (EuRAD) (pp. 119-122). Utrecht, NL: New York City: IEEE.

MLA:

Fröhlich, Ann-Christine, and Ingrid Ullmann. "A Dataset on Human Activity Recognition with a Multistatic Radar Network." Proceedings of the 2025 22nd European Radar Conference (EuRAD), Utrecht New York City: IEEE, 2025. 119-122.

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