Simultaneous Localization and Mapping (SLAM) for Room Exploration Using Ultrawideband Millimeterwave FMCW Radar

<u>S</u>imultaneous <u>L</u>ocalization <u>a</u>nd <u>M</u>apping (SLAM) of indoor scenarios is usually based on camera or lidar sensors as data sources. However, radar based room scanning offers several complementary advantages to these systems. Among other features, radar sensors are more robust to optical opacities, for example, those caused by smoke and dust in emergency scenarios or in harsh environments. Furthermore, the coherent measurement principle of radar sensors provides highly precise distance information that can be utilized to track the exact position and dimensions of the visible objects. In contrast to camera and lidar, radar applications in room exploration are up to now limited by reduced spatial, i.e. mostly angular/lateral, resolution. This is due to the comparably large wavelength of the utilized signals. This work demonstrates the capabilities of ultrawideband millimeterwave <u>F</u>requency <u>M</u>odulated <u>C</u>ontinuous <u>W</u>ave (FMCW) radar sensors operating around 80 GHz in conjunction with the <u>S</u>ynthetic <u>A</u>perture <u>R</u>adar (SAR) imaging method. To allow imaging whilst moving, self-localization techniques based on sub-aperture processing are evaluated. Therefore, we demonstrate a detailed mapping procedure for room exploration applications by exploiting large absolute bandwidths of more than 20 GHz with high resolution imaging techniques on a mobile robot platform.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Microwaves
Published
2025-03-01
DOI
https://doi.org/10.1109/jmw.2025.3541789
Citations
1
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.73

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Simultaneous Localization and Mapping (SLAM) for Room Exploration Using Ultrawideband Millimeterwave FMCW Radar

Christian Schulz, Nils Pohl, Ilona Rolfes, Jan Barowski et al.
1 citations
IEEE Journal of Microwaves
Indoor and Outdoor Localization Technologies
0.73
article

Simultaneous Localization and Mapping (SLAM) for Room Exploration Using Ultrawideband Millimeterwave FMCW Radar

Christian Schulz, Nils Pohl, Ilona Rolfes, Jan Barowski, Thomas Kaiser, Aman Batra, Tobias Körner
article en
1 citations

Abstract

<u>S</u>imultaneous <u>L</u>ocalization <u>a</u>nd <u>M</u>apping (SLAM) of indoor scenarios is usually based on camera or lidar sensors as data sources. However, radar based room scanning offers several complementary advantages to these systems. Among other features, radar sensors are more robust to optical opacities, for example, those caused by smoke and dust in emergency scenarios or in harsh environments. Furthermore, the coherent measurement principle of radar sensors provides highly precise distance information that can be utilized to track the exact position and dimensions of the visible objects. In contrast to camera and lidar, radar applications in room exploration are up to now limited by reduced spatial, i.e. mostly angular/lateral, resolution. This is due to the comparably large wavelength of the utilized signals. This work demonstrates the capabilities of ultrawideband millimeterwave <u>F</u>requency <u>M</u>odulated <u>C</u>ontinuous <u>W</u>ave (FMCW) radar sensors operating around 80 GHz in conjunction with the <u>S</u>ynthetic <u>A</u>perture <u>R</u>adar (SAR) imaging method. To allow imaging whilst moving, self-localization techniques based on sub-aperture processing are evaluated. Therefore, we demonstrate a detailed mapping procedure for room exploration applications by exploiting large absolute bandwidths of more than 20 GHz with high resolution imaging techniques on a mobile robot platform.

IEEE Journal of MicrowavesVol. 5(2)
University of Duisburg-Essen (DE), Ruhr University Bochum (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 31%
Indoor and Outdoor Localization Technologies
0.73
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.