mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting

Indoor mmWave-based sensing technologies have garnered substantial interest from both the industrial and academic. Yet, the intrinsic challenge posed by the limited Field-of-View (FOV) of mmWave radars significantly restricts their coverage. This limitation necessitates careful selection of installation positions and orientations to optimize performance, thereby severely curtailing the versatility and widespread adoption of these systems. Traditionally, expanding coverage involved increasing the number of radar units. This paper introduces a novel approach to enhance the FOV by incorporating mobility, achieved by affixing the radar onto a pan-tilt unit capable of rotating along both the horizontal and azimuthal. Nevertheless, the disparity between the pan-tilt and the radar presents significant challenges for accurately rotating the radar's orientation. To mitigate this, we propose an automated calibration algorithm for radar and pan-tilt, ensuring precise calibration. Additionally, we have devised a radar orientation adjustment algorithm intended to automatically align the radar's FOV with the positions of detected objects to facilitate various applications. Through three case studies, we have demonstrated that mmRotation can greatly expand the sensing range, enabling support for multiple applications on a single radar, such as vital signs monitoring and fall detection. Comprehensive experimental results underscore that our system surpasses the current state-of-the-art (SOTA).

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Publication Details

Journal
IEEE Transactions on Mobile Computing
Published
2025-02-07
DOI
https://doi.org/10.1109/tmc.2025.3539985
Citations
4
Primary Topic
Radio Wave Propagation Studies
Type
article
Field-Weighted Citation Impact
19.97
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article

mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting

Yaxiong Xie, Duo Zhang, Zhenhua Yin, Daqing Zhang et al.
4 citations
IEEE Transactions on Mobile Computing
Radio Wave Propagation Studies
19.97
article

mmRotation: Unlocking Versatility of a Single mmWave Radar via Azimuth Panning and Elevation Tilting

Yaxiong Xie, Duo Zhang, Zhenhua Yin, Daqing Zhang, Hewen Wei, Zhaoxin Chang, Xusheng Zhang, Wenwei Li
article en
4 citations

Abstract

Indoor mmWave-based sensing technologies have garnered substantial interest from both the industrial and academic. Yet, the intrinsic challenge posed by the limited Field-of-View (FOV) of mmWave radars significantly restricts their coverage. This limitation necessitates careful selection of installation positions and orientations to optimize performance, thereby severely curtailing the versatility and widespread adoption of these systems. Traditionally, expanding coverage involved increasing the number of radar units. This paper introduces a novel approach to enhance the FOV by incorporating mobility, achieved by affixing the radar onto a pan-tilt unit capable of rotating along both the horizontal and azimuthal. Nevertheless, the disparity between the pan-tilt and the radar presents significant challenges for accurately rotating the radar's orientation. To mitigate this, we propose an automated calibration algorithm for radar and pan-tilt, ensuring precise calibration. Additionally, we have devised a radar orientation adjustment algorithm intended to automatically align the radar's FOV with the positions of detected objects to facilitate various applications. Through three case studies, we have demonstrated that mmRotation can greatly expand the sensing range, enabling support for multiple applications on a single radar, such as vital signs monitoring and fall detection. Comprehensive experimental results underscore that our system surpasses the current state-of-the-art (SOTA).

IEEE Transactions on Mobile ComputingVol. 24(7)
Peking University (CN), Institute of Software (CN), Institut Polytechnique de Paris (FR), University at Buffalo, State University of New York (US)
Affordable and clean energy
Openalex Percentile: Top 1%
Radio Wave Propagation Studies
19.97
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