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Multistage algorithms for extended dwell target detection

机译:用于扩展驻留目标检测的多级算法

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Improvements in detecting weak targets from a small radar platform must come through increased temporal integration, i.e., extending the time over which target samples are coherently integrated. Conventional single-channel radar assumes a linear-phase signal model that is only accurate over a short dwell time for typical target motion. Over an extended dwell, the target signal includes multiple nonlinear phase components, each of whose effects become significant at different times during the dwell. An algorithm is presented that develops a multiphase signal model in multiple stages based on these times. A modification of the proposed approach improves the signal model for the most challenging targets. When used as the detection filter, the multiphase signal model yields near optimal performance over an extended dwell time for a wide range of target parameters. Typical improvement in output signal-to-noise ratio (SNR) for a 500 ms dwell is 12–13 dB over conventional processing.
机译:检测来自小雷达平台的弱目标的改进必须通过增加的时间积分,即,扩展目标样本的连贯整合的时间。传统的单通道雷达假设线性相位信号模型,该模型仅在典型目标运动的短期停留时间上精确。在延长的停留中,目标信号包括多个非线性相位分量,每个非线性相位分量在居住期间在不同时间变得显着。提出了一种算法,其基于这些时间在多个阶段中开发多相信号模型。提出方法的修改改善了最具挑战性目标的信号模型。当用作检测滤波器时,多相信号模型在广泛的目标参数上通过扩展停留时间产生近最佳性能。 500ms DWELT的输出信噪比(SNR)的典型改进是传统处理的12-13 dB。

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