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雷达卡
摘要翻译：
本文提出了一种在不依赖人携带任何设备的情况下，使用WiFi设备估计人群速度的方法。我们的方法不仅可以在有WiFi链路的区域进行速度估计，而且可以在邻近的可能没有WiFi链路的区域进行速度估计。更具体地说，我们在一个区域使用一对WiFi链路，然后使用其RSSI测量来估计人群速度，不仅在该区域，而且在邻近的无WiFi区域。我们首先证明了交叉相关性和通过两个链路的概率是如何隐含行人速度的关键信息的，并建立了将它们与行人速度相关联的数学模型。然后，我们在室内和室外的108个实验中验证了我们的方法，其中多达10人在两个相邻区域行走，每个区域的速度不同，表明我们的框架可以在一个区域中只使用一对WiFi链接就准确地估计这些速度。例如，所有实验的NMSE为0.18。我们还在博物馆类型的设置中评估我们的框架，并估计不同展品的受欢迎程度。最后，我们在好市多的一个过道上进行了实验，估计了买家行为的关键属性。
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英文标题：
《Passive Crowd Speed Estimation in Adjacent Regions With Minimal WiFi
Sensing》
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作者：
Saandeep Depatla and Yasamin Mostofi
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最新提交年份：
2018
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分类信息：
一级分类：Electrical Engineering and Systems Science 电气工程与系统科学
二级分类：Signal Processing 信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science 计算机科学
二级分类：Networking and Internet Architecture 网络和因特网体系结构
分类描述：Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
涵盖计算机通信网络的所有方面，包括网络体系结构和设计、网络协议和网络间标准（如TCP/IP）。还包括与Internet体系结构和性能直接相关的主题，如web缓存。大致包括除C.2.4以外的所有ACM主题类C.2，后者更有可能将分布式、并行和集群计算作为主要主题领域。
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英文摘要：
In this paper, we propose a methodology for estimating the crowd speed using WiFi devices without relying on people to carry any device. Our approach not only enables speed estimation in the region where WiFi links are, but also in the adjacent possibly WiFi-free regions. More specifically, we use a pair of WiFi links in one region, whose RSSI measurements are then used to estimate the crowd speed, not only in this region, but also in adjacent WiFi-free regions. We first prove how the cross-correlation and the probability of crossing the two links implicitly carry key information about the pedestrian speeds and develop a mathematical model to relate them to pedestrian speeds. We then validate our approach with 108 experiments, in both indoor and outdoor, where up to 10 people walk in two adjacent areas, with variety of speeds per region, showing that our framework can accurately estimate these speeds with only a pair of WiFi links in one region. For instance, the NMSE over all experiments is 0.18. We also evaluate our framework in a museum-type setting and estimate the popularity of different exhibits. We finally run experiments in an aisle in Costco, estimating key attributes of buyers' behaviors.
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PDF链接：
https://arxiv.org/pdf/1711.05855
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