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    • 3. 发明授权
    • GNSS signal processing to estimate orbits
    • GNSS信号处理估计轨道
    • US08847820B2
    • 2014-09-30
    • US13393202
    • 2010-09-19
    • Herbert LandauMarkus Nitschke
    • Herbert LandauMarkus Nitschke
    • G01S19/27G01S19/43G01S19/04G01S19/25
    • G01S19/04G01S19/20G01S19/258G01S19/37G01S19/43
    • Methods and apparatus are described for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising: obtaining an orbit start vector comprising: a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters, obtaining ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and iteratively correcting the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionospheric-free linear combinations of the epoch are available, to obtain updated orbit start vector values comprising a time sequence of predicted positions and predicted velocities for each satellite over a subsequent interval of epochs and an estimate of Earth orientation parameters.
    • 描述了用于处理从在参考站接收机处观测到的GNSS卫星的信号导出的一组GNSS信号数据的方法和装置,代表代表观测的数据和在多个时期的至少两个载波上的载波观测,包括:获得轨道开始 包括:在第一间隔上每个卫星的预测位置和预测速度的时间序列,以及相对于初始位置,初始速度,力模型参数和接地取向参数的预测位置和预测速度的偏导数,获得电离层 - 在多个参考站的每个卫星的代码观测和载波观测的自由线性组合,以及在每个时刻使用电离层无线性组合和预测的地球取向参数迭代地校正轨道起始向量,一旦电离层无 线性组合的ep och可用于获得更新的轨道起始向量值,其包括在随后的时间间隔中的每个卫星的预测位置和预测速度的时间序列和地球取向参数的估计。
    • 5. 发明授权
    • Risk management for object identification
    • 对象识别的风险管理
    • US08595177B1
    • 2013-11-26
    • US13042699
    • 2011-03-08
    • Kenric P. NelsonBrian J. ScannellHerbert Landau
    • Kenric P. NelsonBrian J. ScannellHerbert Landau
    • G06F9/44
    • G01S13/723G01S7/41
    • The technology described herein includes a system and/or a method of risk management for object identification. The method includes selecting at least two fusion functions from a plurality of fusion functions. Each of the fusion functions is associated with a different risk bias. The method further includes fusing a received set of data based on each fusion function to form at least two sets of fused data. The method further includes generating a probability of identification of the classification of the object based on each set of the fused data. The method further includes determining a risk bias difference between the probability of identification of each set of the fused data.
    • 本文描述的技术包括用于物体识别的系统和/或风险管理方法。 该方法包括从多个融合函数中选择至少两个融合函数。 每个融合功能与不同的风险偏差相关联。 该方法还包括基于每个融合功能融合接收到的一组数据以形成至少两组融合数据。 该方法还包括基于每组融合数据生成识别对象分类的概率。 该方法还包括确定识别每组融合数据的概率之间的风险偏差差异。
    • 6. 发明申请
    • GNSS Signal Processing to Estimate Orbits
    • GNSS信号处理估计轨道
    • US20120154210A1
    • 2012-06-21
    • US13393202
    • 2010-09-19
    • Herbert LandauMarkus Nitschke
    • Herbert LandauMarkus Nitschke
    • G01S19/40
    • G01S19/04G01S19/20G01S19/258G01S19/37G01S19/43
    • Methods and apparatus are described for processing a set of GNSS signal data derived from signals of GNSS satellites observed at reference station receivers, the data representing code observations and carrier observations on each of at least two carriers over multiple epochs, comprising: obtaining an orbit start vector comprising: a time sequence of predicted positions and predicted velocities for each satellite over a first interval, and the partial derivatives of the predicted positions and predicted velocities with respect to initial positions, initial velocities, force model parameters and Earth orientation parameters, obtaining ionospheric-free linear combinations of the code observations and the carrier observations for each satellite at multiple reference stations, and iteratively correcting the orbit start vector using at each epoch the ionospheric-free linear combinations and predicted Earth orientation parameters, as soon as the ionspheric-free linear combinations of the epoch are available, to obtain updated orbit start vector values comprising a time sequence of predicted positions and predicted velocities for each satellite over a subsequent interval of epochs and an estimate of Earth orientation parameters.
    • 描述了用于处理从在参考站接收机处观测到的GNSS卫星的信号导出的一组GNSS信号数据的方法和装置,代表代表观测的数据和在多个时期的至少两个载波上的载波观测,包括:获得轨道开始 包括:在第一间隔上每个卫星的预测位置和预测速度的时间序列,以及相对于初始位置,初始速度,力模型参数和接地取向参数的预测位置和预测速度的偏导数,获得电离层 - 在多个参考站的每个卫星的代码观测和载波观测的自由线性组合,以及在每个时刻使用电离层无线性组合和预测的地球取向参数迭代地校正轨道起始向量,一旦无离子 线性组合的epo ch可用于获得更新的轨道起始向量值,其包括在随后的时代间隔中的每个卫星的预测位置和预测速度的时间序列以及地球定向参数的估计。
    • 8. 发明授权
    • Associating observations in a multi-sensor system using an adaptive gate value
    • 使用自适应门值在多传感器系统中关联观测值
    • US07941292B2
    • 2011-05-10
    • US12114134
    • 2008-05-02
    • Ronald R. KusnerHerbert LandauJohn-David Sergi
    • Ronald R. KusnerHerbert LandauJohn-David Sergi
    • G06F17/18G06F15/00
    • G01S13/726G06K9/6289G06K9/6298
    • In one aspect, a method to assign observations includes receiving first observations of a first sensor system, receiving second observations of a second sensor system and assigning a set of pairs of the first and second observations predicted to correspond to the same physical position. The assigning includes using a likelihood function that specifies a likelihood for each assigned pair. The likelihood is dependent on the assignment of any other assigned pairs in the set of assigned pairs. The assigning also includes determining the set of assigned pairs for the first and second observations based on the likelihood function. The likelihood function uses a gate value determined from estimating a true volume using nearest neighbor distances determined from the first and second observations.
    • 在一个方面,一种用于分配观测值的方法包括:接收第一传感器系统的第一观测值,接收第二传感器系统的第二观测值,以及分配预测的一组第一和第二观测值对应于相同的物理位置。 分配包括使用为每个分配对指定似然性的似然函数。 可能性取决于分配对集合中任何其他分配对的分配。 分配还包括基于似然函数确定用于第一和第二观测的分配对的集合。 似然函数使用从通过从第一和第二观察确定的最近邻距离估计真实体积确定的门值。