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DRMTrack: An Extended Distributed Millimeter-Wave Radar Framework for Indoor Multitarget Human Trajectory Tracking
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DOI：10.1109/JIOT.2025.3594120.png)
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Abstract
En 中文
Most researches on indoor target trajectory tracking using millimeter-wave radar have faced challenges, such as interference from multipath effects, which led to corrupted point clouds, and large tracking errors in multitarget scenarios. This study aims to improve the accuracy of human multiple-object tracking, addressing the practical challenges of target trajectory tracking in indoor environments. We proposed an extended distributed radar multitarget tracking (DRMTrack) framework that enabled the fusion of point clouds from multiple radar nodes. Additionally, by exploiting the spatial distribution characteristics of the target point clouds for clustering, tracking filtering and integrating historical data for tracking association, the framework enhances multiple-object trajectory tracking performance. Experimental results demonstrate that for various trajectory paths, the minimum position tracking error for multitarget is 5.2 cm. In the five-target tracking scenario, the 90th percentile tracking error is 18.8 cm, representing a 27.7% improvement in accuracy compared to single-radar tracking. The DRMTrack system effectively reduces interference from clutter point clouds, enhances multiple-object tracking precision, and supports real-time computation. This system is suitable for motion monitoring in indoor environments, such as homes and hospital rooms, effectively fulfilling the needs of real-time, noncontact health management.
Keywords:
Distributed
millimeter-wave radar
multitarget classification
multitarget tracking
point cloud fusion
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