LoCal

IF 3.6 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Pub Date : 2024-01-12 DOI:10.1145/3631436
Duo Zhang, Xusheng Zhang, Yaxiong Xie, Fusang Zhang, Xuanzhi Wang, Yang Li, Daqing Zhang
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引用次数: 0

摘要

毫米波(mmWave)雷达在准确估计信号反射器相对于雷达的距离、速度和角度方面表现出色。然而,对于依赖雷达跟踪能力的各种传感应用来说,这些估计值必须从雷达转换到室内坐标。这种转换取决于毫米波雷达的位置属性,包括其在房间坐标中的位置和方向。传统的自动驾驶室外校准解决方案利用角反射器作为静态参考点来推导位置属性。在室内环境中部署时,即使是具有 GHz 带宽和大型天线阵列的毫米波雷达,要将静态参考点与其他多径反射体分开也是一项挑战。为了解决静态多径问题,我们建议部署一个移动参考点(移动机器人),以充分利用毫米波雷达的速度分辨率。具体来说,我们选择一个具有 SLAM 功能的机器人,以便在运动过程中根据房间坐标准确获取其位置,而无需人工干预。在两个坐标系下精确配对机器人的位置需要毫米波雷达和机器人之间的紧密同步。因此,我们提出了一种基于轨迹对应的新型校准算法,该算法将两个系统的估计轨迹作为输入,最大限度地解耦了两个系统的操作。广泛的实验结果表明,所提出的校准解决方案具有极高的精度(定位和定向精度分别为 1.74 厘米和 0.43°),可确保在跌倒检测、点云融合和远距离人体跟踪这三个具有代表性的应用中发挥出色的性能。
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LoCal
Millimeter wave (mmWave) radar excels in accurately estimating the distance, speed, and angle of the signal reflectors relative to the radar. However, for diverse sensing applications reliant on radar's tracking capability, these estimates must be transformed from radar to room coordinates. This transformation hinges on the mmWave radar's location attribute, encompassing its position and orientation in room coordinates. Traditional outdoor calibration solutions for autonomous driving utilize corner reflectors as static reference points to derive the location attribute. When deployed in the indoor environment, it is challenging, even for the mmWave radar with GHz bandwidth and a large antenna array, to separate the static reference points from other multipath reflectors. To tackle the static multipath, we propose to deploy a moving reference point (a moving robot) to fully harness the velocity resolution of mmWave radar. Specifically, we select a SLAM-capable robot to accurately obtain its locations under room coordinates during motion, without requiring human intervention. Accurately pairing the locations of the robot under two coordinate systems requires tight synchronization between the mmWave radar and the robot. We therefore propose a novel trajectory correspondence based calibration algorithm that takes the estimated trajectories of two systems as input, decoupling the operations of two systems to the maximum. Extensive experimental results demonstrate that the proposed calibration solution exhibits very high accuracy (1.74 cm and 0.43° accuracy for location and orientation respectively) and could ensure outstanding performance in three representative applications: fall detection, point cloud fusion, and long-distance human tracking.
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来源期刊
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Computer Science-Computer Networks and Communications
CiteScore
9.10
自引率
0.00%
发文量
154
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