通过连续声波追踪房间尺度的位置轨迹

IF 3.9 4区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on Sensor Networks Pub Date : 2024-02-20 DOI:10.1145/3649136
Jie Lian, Xu Yuan, Jiadong Lou, Li Chen, Hao Wang, Nianfeng Tzeng
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引用次数: 0

摘要

智能设备的日益普及推动了新兴室内定位技术的发展,以支持家庭中的各种个性化应用。鉴于流行的基于啁啾信号的方法存在明显缺陷,我们旨在通过不可听频率的连续波开发一种新型的无设备定位系统。为实现这一目标,我们开发了细粒度分析解决方案,能够精确定位房间尺度环境中移动的人体痕迹。特别是,我们控制智能扬声器发射 20kHz 不可听频率的连续波,并通过共定位麦克风阵列记录其多普勒反射以进行定位。我们首先开发了消除潜在噪声的解决方案,然后提出了一个新颖的想法,即把信号切成一组窄带信号,每组窄带信号可能最多包含一个体段的反射。与以往将原始信号本身作为基带的研究不同,我们的解决方案首先利用窄带信号的多普勒频率来估算速度,然后将其用于获得精确的基带频率,这样就可以在 I-Q(即同相和正交)分解后进行精确的相位测量。然后,我们建立了一个信号模型,该模型能够根据体段的速度、范围和角度来确定相位。接下来,我们开发了新颖的解决方案来估计每个窄带信号中的运动状态,对同一人对应的不同身体段的运动状态进行聚类,并在减轻多路径效应的同时定位运动轨迹。我们的系统是在室内环境中使用商品设备实现的,以进行性能评估。实验结果表明,我们的系统可以对房间中的多达三个人进行有效定位,单人的平均误差为 7.49 厘米,两人的平均误差为 24.06 厘米,三人的平均误差为 51.15 厘米。
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Room-Scale Location Trace Tracking via Continuous Acoustic Waves

The increasing prevalence of smart devices spurs the development of emerging indoor localization technologies for supporting diverse personalized applications at home. Given marked drawbacks of popular chirp signal-based approaches, we aim to develop a novel device-free localization system via the continuous wave of the inaudible frequency. To achieve this goal, solutions are developed for fine-grained analyses, able to precisely locate moving human traces in the room-scale environment. In particular, a smart speaker is controlled to emit continuous waves at inaudible 20kHz, with a co-located microphone array to record their Doppler reflections for localization. We first develop solutions to remove potential noises and then propose a novel idea by slicing signals into a set of narrowband signals, each of which is likely to include at most one body segment’s reflection. Different from previous studies, which take original signals themselves as the baseband, our solutions employ the Doppler frequency of a narrowband signal to estimate the velocity first and apply it to get the accurate baseband frequency, which permits a precise phase measurement after I-Q (i.e., in-phase and quadrature) decomposition. A signal model is then developed, able to formulate the phase with body segment’s velocity, range, and angle. We next develop novel solutions to estimate the motion state in each narrowband signal, cluster the motion states for different body segments corresponding to the same person, and locate the moving traces while mitigating multi-path effects. Our system is implemented with commodity devices in room environments for performance evaluation. The experimental results exhibit that our system can conduct effective localization for up to three persons in a room, with the average errors of 7.49cm for a single person, with 24.06cm for two persons, with 51.15cm for three persons.

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来源期刊
ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks 工程技术-电信学
CiteScore
5.90
自引率
7.30%
发文量
131
审稿时长
6 months
期刊介绍: ACM Transactions on Sensor Networks (TOSN) is a central publication by the ACM in the interdisciplinary area of sensor networks spanning a broad discipline from signal processing, networking and protocols, embedded systems, information management, to distributed algorithms. It covers research contributions that introduce new concepts, techniques, analyses, or architectures, as well as applied contributions that report on development of new tools and systems or experiences and experiments with high-impact, innovative applications. The Transactions places special attention on contributions to systemic approaches to sensor networks as well as fundamental contributions.
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