Automatic matched Doppler filter selection
    1.
    发明授权
    Automatic matched Doppler filter selection 有权
    自动匹配多普勒滤波器选择

    公开(公告)号:US08970426B1

    公开(公告)日:2015-03-03

    申请号:US13678045

    申请日:2012-11-15

    CPC classification number: G01S13/5244 G01S13/28

    Abstract: A system for suppressing clutter in a radar system is provided. The system includes an antenna configured to receive radar signals containing clutter and a digital receiver adapted to convert the radar signals received by the radar arrays to complex I/Q samples. These I/Q samples are provided to a Doppler filter bank comprising a plurality of Doppler filters for filtering the pulse compressed data into Doppler bins representative of range values according to Doppler frequency. The system further includes at least one processor for comparing the output of each of the plurality of Doppler filters types to respective background clutter maps, and identifying the Doppler filter which outputs the radar return signal with the greatest magnitude over the clutter map. Once identified, target detection operations may be performed on the output of the identified Doppler filter.

    Abstract translation: 提供了一种用于抑制雷达系统中杂波的系统。 该系统包括被配置为接收包含杂波的雷达信号的天线和适于将由雷达阵列接收的雷达信号转换成复杂I / Q样本的数字接收机。 将这些I / Q样本提供给包括多个多普勒滤波器的多普勒滤波器组,用于根据多普勒频率将脉冲压缩数据过滤到表示范围值的多普勒频带。 该系统还包括至少一个处理器,用于将多个多普勒滤波器类型中的每一个的输出与相应的背景杂波图进行比较,以及识别在杂波图上输出最大幅度的雷达返回信号的多普勒滤波器。 一旦识别,可以对所识别的多普勒滤波器的输出执行目标检测操作。

    Three dimensional direction finder with one dimensional sensor array

    公开(公告)号:US09995817B1

    公开(公告)日:2018-06-12

    申请号:US14692192

    申请日:2015-04-21

    Inventor: David M. Mittiga

    CPC classification number: G01S5/0294 G01B21/22 G01S3/04 G01S5/0018 G01S5/16

    Abstract: A tracking computer system may track a target using a single linear array. The system may receive first sensor measurements and one or more additional sensor measurements from the linear array. The system may determine whether a location of the target can be identified based on a cone intersection algorithm. When the target location can be identified based on the cone intersection algorithm, the first and the one or more additional sensor measurements may be applied to the cone intersection algorithm to identify the target location. When target location cannot be identified based on the cone intersection algorithm, the first and the one or more additional sensor measurements may be applied to an angular motion model to determine a best fit arc path corresponding to the target. A true target angle estimate and a target angular velocity may be determined based on the determined best fit arc path.

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