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    • 1. 发明申请
    • Method and Network for Determining Positions of Wireless Nodes While Minimizing Propagation of Positioning Errors
    • 确定无线节点位置的方法和网络,同时最大限度地减少定位误差的传播
    • US20110074569A1
    • 2011-03-31
    • US12571399
    • 2009-09-30
    • Nayef AlsindiChunjie DuanJinyun Zhang
    • Nayef AlsindiChunjie DuanJinyun Zhang
    • G08B1/08
    • G01S5/0289
    • A wireless sensor network includes an initial set of anchors at known locations, and a set of sensors at unknown locations. Ranges, from each sensor to at least three of the anchors, determine a position, an anchor ranging weight, and an anchor position weight. For each anchor, the anchor ranging weight and the anchor position weight form a combined weight. A weighted least square (WLS) function for the positions and the combined weights is minimized to determine a position of the sensor, and a sensor position weight. The sensor is identified as being a member of a set of candidate anchor nodes, and the candidate anchor node with a largest sensor position weight is selected to be transformed to another anchor to minimize propagation of errors in the positions of the set of sensors.
    • 无线传感器网络包括在已知位置处的初始锚点集合,以及在未知位置处的一组传感器。 从每个传感器到至少三个锚的范围确定位置,锚定测距重量和锚定位置重量。 对于每个锚,锚定距离权重和锚位置权重形成组合重量。 用于位置和组合权重的加权最小二乘(WLS)功能被最小化以确定传感器的位置和传感器位置权重。 传感器被识别为一组候选锚节点的成员,并且选择具有最大传感器位置权重的候选锚节点以被变换到另一个锚点,以最小化传感器组中位置误差的传播。
    • 2. 发明授权
    • Method and network for determining positions of wireless nodes while minimizing propagation of positioning errors
    • 用于确定无线节点的位置同时最小化定位误差传播的方法和网络
    • US08179251B2
    • 2012-05-15
    • US12571399
    • 2009-09-30
    • Nayef AlsindiChunjie DuanJinyun Zhang
    • Nayef AlsindiChunjie DuanJinyun Zhang
    • G08B1/08
    • G01S5/0289
    • A wireless sensor network includes an initial set of anchors at known locations, and a set of sensors at unknown locations. Ranges, from each sensor to at least three of the anchors, determine a position, an anchor ranging weight, and an anchor position weight. For each anchor, the anchor ranging weight and the anchor position weight form a combined weight. A weighted least square (WLS) function for the positions and the combined weights is minimized to determine a position of the sensor, and a sensor position weight. The sensor is identified as being a member of a set of candidate anchor nodes, and the candidate anchor node with a largest sensor position weight is selected to be transformed to another anchor to minimize propagation of errors in the positions of the set of sensors.
    • 无线传感器网络包括在已知位置处的初始锚点集合,以及在未知位置处的一组传感器。 从每个传感器到至少三个锚的范围确定位置,锚定测距重量和锚定位置重量。 对于每个锚,锚定距离权重和锚位置权重形成组合重量。 用于位置和组合权重的加权最小二乘(WLS)功能被最小化以确定传感器的位置和传感器位置权重。 传感器被识别为一组候选锚节点的成员,并且选择具有最大传感器位置权重的候选锚节点以被变换到另一个锚点,以最小化传感器组中位置误差的传播。
    • 10. 发明申请
    • Methods and apparatus for narrow band interference detection and suppression in ultra-wideband systems
    • 超宽带系统中窄带干扰检测和抑制的方法和装置
    • US20100246635A1
    • 2010-09-30
    • US12385078
    • 2009-03-30
    • Zhenzhen YeChunjie DuanPhilip OrlikJinyun Zhang
    • Zhenzhen YeChunjie DuanPhilip OrlikJinyun Zhang
    • H04B1/69H04B1/10
    • H04J11/0066H04B1/719
    • An exemplary method is disclosed to accurately estimate the center frequency of a narrow-band interference (NBI). The exemplary method uses multi-stage autocorrelation-function (ACF) to estimate an NBI frequency. The exemplary method allows an accurate estimation of the center frequency of NBI in an Ultra-Wideband system. A narrow band interference (NBI) estimator based on such a method allows a low complexity hardware implementation. The exemplary method estimates the frequency in multiple stages. Each stage performs an ACF operation on the received signals. The first stage gives an initial estimation and the following stages refine the estimation. The results of all stages are combined to produce the final estimation. An apparatus based on such a multi-stage narrow band interference frequency detector is also disclosed to improve the accuracy by combining various filters with the detector.
    • 公开了一种用于精确估计窄带干扰(NBI)的中心频率的示例性方法。 该示例性方法使用多级自相关函数(ACF)来估计NBI频率。 该示例性方法允许在超宽带系统中准确估计NBI的中心频率。 基于这种方法的窄带干扰(NBI)估计器允许低复杂度的硬件实现。 该示例性方法以多个阶段估计频率。 每个级对所接收的信号执行ACF操作。 第一阶段给出初步估计,并且以下阶段改进估计。 结合所有阶段的结果进行最终估计。 还公开了一种基于这种多级窄带干扰频率检测器的装置,通过将各种滤波器与检测器组合来提高精度。