Localization of Wireless Terminals via Deep Learning

通过深度学习定位无线终端

基本信息

  • 批准号:
    RGPIN-2017-06625
  • 负责人:
  • 金额:
    $ 2.04万
  • 依托单位:
  • 依托单位国家:
    加拿大
  • 项目类别:
    Discovery Grants Program - Individual
  • 财政年份:
    2018
  • 资助国家:
    加拿大
  • 起止时间:
    2018-01-01 至 2019-12-31
  • 项目状态:
    已结题

项目摘要

Localization of wireless terminals has gained momentum over the last few years. Many applications are now being developed that provide location based services. Google map, Find My iPhone, Virtual Reality Headsets, and Pokémon Go are some examples of applications that use location information. Various new applications will be developed when 5G, Internet-of-Things, and Smart Cities technologies become available. Unfortunately, the GPS service is not available in indoors, or is very inaccurate in areas blocked by tall buildings such as downtown cores in major cities. New technologies should be developed to complement GPS and provide location estimation ubiquitously. ******Our research at the University of Toronto has been on location finding in recent past. We have developed new localization technologies based on received signal strength (RSS) using advance signal processing methods such as Compressive Sensing. We have studied WiFi received signal strength based localizations and tracking, device diversity through unsupervised learning, and crowdsourcing. We have two patented technologies and a pending patent application. Currently, we are working on location finding via image and video signal processing. ******The proposed research activity will be the continuation and refinement of our previous research. New studies have shown that using channel state information (CSI) of WiFi signals can give a significant gain in location accuracy, and that a single access point is sufficient to have decimeter level localization accuracy. There are, however, a few shortcomings in the reported literature that limits the application of these methods in practice. The method is only applicable to a pair of nodes, uses the whole ISM band in 2.4 GHz and 5.8 GHz, and its range is limited. Our work will answer some of the open problems in the application of CSI. We will use Deep Learning methods for location finding on RSS and CSI. Deep learning has gained momentum in tackling difficult problems such as voice and video classification, big data, and medical imaging. A deep neural network can extract a wide range of complex features that can be used in regression and classification. Our goal is to develop effective location finding methods that can locate users at decimeter level accuracy operating on off-the-shelf phones without any specialized hardware. **
无线终端的本地化在过去几年中获得了动力。现在正在开发许多提供基于位置的服务的应用。Google地图、Find My iPhone、Virtual Reality Headsets和Pokémon Go是使用位置信息的应用程序的一些示例。当5G、物联网和智慧城市技术可用时,将开发各种新的应用。不幸的是,GPS服务在室内不可用,或者在被高层建筑阻挡的区域(如主要城市的市中心)非常不准确。应开发新技术,以补充全球定位系统,并提供无处不在的位置估计。** 我们在多伦多大学的研究一直在寻找位置在最近的过去。我们开发了基于接收信号强度(RSS)的新定位技术,使用先进的信号处理方法,如压缩感知。我们研究了基于WiFi接收信号强度的定位和跟踪,通过无监督学习的设备多样性和众包。我们拥有两项专利技术和一项正在申请的专利。目前,我们正在通过图像和视频信号处理进行定位。* *新的研究表明,使用WiFi信号的信道状态信息(CSI)可以显著提高定位精度,并且单个接入点足以具有分米级的定位精度。然而,有一些缺点,在文献报道,限制了这些方法在实践中的应用。该方法只适用于一对节点,使用2.4 GHz和5.8 GHz的整个ISM频段,范围有限。我们的工作将回答一些开放的问题,在CSI的应用。我们将使用深度学习方法在RSS和CSI上进行定位。深度学习在解决语音和视频分类、大数据和医学成像等难题方面取得了进展。深度神经网络可以提取广泛的复杂特征,这些特征可用于回归和分类。我们的目标是开发有效的定位方法,可以定位用户在分米级的精度操作现成的电话,没有任何专门的硬件。 **

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

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Valaee, Shahrokh其他文献

Landmark Graph-Based Indoor Localization
  • DOI:
    10.1109/jiot.2020.2989501
  • 发表时间:
    2020-09-01
  • 期刊:
  • 影响因子:
    10.6
  • 作者:
    Gu, Fuqiang;Valaee, Shahrokh;Zhang, Rui
  • 通讯作者:
    Zhang, Rui
Vehicular node localization using received-signal-strength indicator
A Survey on Behavior Recognition Using WiFi Channel State Information
  • DOI:
    10.1109/mcom.2017.1700082
  • 发表时间:
    2017-10-01
  • 期刊:
  • 影响因子:
    11.2
  • 作者:
    Yousefi, Siamak;Narui, Hirokazu;Valaee, Shahrokh
  • 通讯作者:
    Valaee, Shahrokh
Diversified viral marketing: The power of sharing over multiple online social networks
  • DOI:
    10.1016/j.knosys.2019.105430
  • 发表时间:
    2020-04-06
  • 期刊:
  • 影响因子:
    8.8
  • 作者:
    Al Abri, Dawood;Valaee, Shahrokh
  • 通讯作者:
    Valaee, Shahrokh
Delay Aware Link Scheduling for Multi-Hop TDMA Wireless Networks
  • DOI:
    10.1109/tnet.2008.2005219
  • 发表时间:
    2009-06-01
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Djukic, Petar;Valaee, Shahrokh
  • 通讯作者:
    Valaee, Shahrokh

Valaee, Shahrokh的其他文献

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{{ truncateString('Valaee, Shahrokh', 18)}}的其他基金

Localization of Wireless Terminals via Deep Learning
通过深度学习定位无线终端
  • 批准号:
    RGPIN-2017-06625
  • 财政年份:
    2021
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Localization of Wireless Terminals via Deep Learning
通过深度学习定位无线终端
  • 批准号:
    RGPIN-2017-06625
  • 财政年份:
    2020
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Localization of Wireless Terminals via Deep Learning
通过深度学习定位无线终端
  • 批准号:
    RGPIN-2017-06625
  • 财政年份:
    2019
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Location-aware Secutiry and Privacy in 5G Wireless Networks
5G 无线网络中的位置感知安全和隐私
  • 批准号:
    494075-2016
  • 财政年份:
    2018
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Strategic Projects - Group
Automatic Training and Radiomap Collection for Indoor Location Estimation
用于室内位置估计的自动训练和无线电地图收集
  • 批准号:
    531951-2018
  • 财政年份:
    2018
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Engage Grants Program
Location-aware Secutiry and Privacy in 5G Wireless Networks
5G 无线网络中的位置感知安全和隐私
  • 批准号:
    494075-2016
  • 财政年份:
    2017
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Strategic Projects - Group
Localization of Wireless Terminals via Deep Learning
通过深度学习定位无线终端
  • 批准号:
    RGPIN-2017-06625
  • 财政年份:
    2017
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Privacy Preserving Location Estimation
隐私保护位置估计
  • 批准号:
    RGPIN-2016-06445
  • 财政年份:
    2016
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Discovery Grants Program - Individual
Location-aware Secutiry and Privacy in 5G Wireless Networks
5G 无线网络中的位置感知安全和隐私
  • 批准号:
    494075-2016
  • 财政年份:
    2016
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Strategic Projects - Group
Automatic vehicule identification using WiFi positioning
利用WiFi定位自动识别车辆
  • 批准号:
    500256-2016
  • 财政年份:
    2016
  • 资助金额:
    $ 2.04万
  • 项目类别:
    Collaborative Research and Development Grants

相似国自然基金

基于Wireless Mesh Network的分布式操作系统研究
  • 批准号:
    60673142
  • 批准年份:
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