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    • 104. 发明授权
    • Classifying wireless signals
    • 分类无线信号
    • US09429647B2
    • 2016-08-30
    • US14097188
    • 2013-12-04
    • Aruba Networks, Inc.
    • Subbu PonnuswamyNethra MuniyappaKiranmaye Sirigineni
    • H04L5/14H04L12/28H04J3/00G01S13/00H04L27/26
    • G01S13/00H04K3/22H04K2203/18H04L27/265H04L27/2666
    • The present disclosure discloses a system and method for. classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.
    • 本公开公开了一种用于的系统和方法。 从傅里叶变换样本分类Wi-Fi信号。 一般来说,从傅里叶变换样本中分类Wi-Fi信号包括:将傅里叶变换样本收集和分割成频率块; 确定傅立叶变换样本的带宽; 以及确定傅里叶变换样本是否对应于窄带信号。 此外,如果确定傅里叶变换样本不对应于窄带信号,则基于FFT样本对应于Wi-Fi信号的确定来计算信道利用率。 如果确定傅里叶变换样本对应于窄带信号,则根据某些标准确定FFT样本对应于Wi-Fi信号。 某些标准可以包括斜率值,子峰值数量,相邻信道的分析,特征匹配或其他标准中的一个或多个。
    • 106. 发明申请
    • VEHICLE PARKING MANAGEMENT DEVICE
    • 车辆停车管理装置
    • US20160110925A1
    • 2016-04-21
    • US14519172
    • 2014-10-21
    • Salem Ali BEN KENAID
    • Salem Ali BEN KENAID
    • G07B15/02G08G1/01
    • G01S19/13G01S13/00G01S19/41G06Q20/145G06Q20/3224G07B15/02G07F17/24G08G1/01H04W40/20H04W64/003
    • Vehicle parking management device comprising an information storage unit adapted to store vehicle identification information allowing to identify the vehicle; a vehicle tracking unit adapted to determine and transmit a location of the vehicle; a vehicle status detection unit adapted to determine a status of the vehicle allowing for determining if the vehicle is in a parking position; a communication unit adapted to be connected to a remote parking management server via a data network; and a vehicle parking management unit adapted to be connected to the information storage unit, to the vehicle tracking unit, to the vehicle status detection unit and to the communication unit for determining if the vehicle is in a parking position and for generating and transmitting to the remote parking management server a parking notification comprising the vehicle identification information and the vehicle location if the vehicle is determined to be in a parking position.
    • 车辆停放管理装置,包括:信息存储单元,适于存储允许识别车辆的车辆识别信息; 车辆跟踪单元,其适于确定和发送所述车辆的位置; 车辆状态检测单元,其适于确定车辆的状态,以允许确定车辆是否在停车位置; 通信单元,适于经由数据网络连接到远程停车管理服务器; 以及车辆停车管理单元,其适于连接到信息存储单元,车辆跟踪单元,车辆状态检测单元和通信单元,用于确定车辆是否在停车位置,并用于生成和发送到 远程停车管理服务器,如果车辆被确定在停车位置,则停车通知包括车辆识别信息和车辆位置。
    • 110. 发明申请
    • CLASSIFYING WIRELESS SIGNALS
    • 分类无线信号
    • US20150156643A1
    • 2015-06-04
    • US14097188
    • 2013-12-04
    • Aruba Networks, Inc.
    • Subbu PonnuswamyNethra MuniyappaKiranmaye Sirigineni
    • H04W24/02
    • G01S13/00H04K3/22H04K2203/18H04L27/265H04L27/2666
    • The present disclosure discloses a system and method for. classifying Wi-Fi signals from Fourier transform samples. Generally, classifying Wi-Fi signals from Fourier transform samples includes: collecting and dividing Fourier transform samples into frequency blocks; determining the bandwidth for the Fourier transform sample; and determining whether the Fourier transform sample corresponds to a narrowband signal. Further, if a determination is made that the Fourier transform sample does not correspond to a narrowband signal, channel utilization is calculated based on a determination that the FFT sample corresponds to a Wi-Fi signal. If it is determined that the Fourier transform sample corresponds to a narrowband signal, then a determination is made that the FFT sample corresponds to a Wi-Fi signal based on certain criteria. The certain criteria may include one or more of a slope value, a number of sub-peak bins, an analysis of adjacent channels, characteristic matching, or other criteria.
    • 本公开公开了一种用于的系统和方法。 从傅里叶变换样本分类Wi-Fi信号。 一般来说,从傅里叶变换样本中分类Wi-Fi信号包括:将傅里叶变换样本收集和分割成频率块; 确定傅立叶变换样本的带宽; 以及确定傅里叶变换样本是否对应于窄带信号。 此外,如果确定傅里叶变换样本不对应于窄带信号,则基于FFT样本对应于Wi-Fi信号的确定来计算信道利用率。 如果确定傅里叶变换样本对应于窄带信号,则根据某些标准确定FFT样本对应于Wi-Fi信号。 某些标准可以包括斜率值,子峰值数量,相邻信道的分析,特征匹配或其他标准中的一个或多个。