扩展驻留目标检测的多阶段算法

A. S. Paulus, W. Melvin, Douglas B. Williams
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引用次数: 3

摘要

从小型雷达平台检测弱目标的改进必须通过增加时间积分来实现,即延长目标样本相干积分的时间。传统的单通道雷达采用线性相位信号模型,该模型仅在典型目标运动的短停留时间内准确。在延长的驻留期间,目标信号包括多个非线性相位分量,每个相位分量的影响在驻留期间的不同时间变得显著。提出了一种基于这些时间建立多阶段多相信号模型的算法。对该方法的改进改进了最具挑战性目标的信号模型。当用作检测滤波器时,多相信号模型在延长的停留时间内对大范围的目标参数产生接近最佳的性能。典型的改善输出信噪比(SNR)的500毫秒驻留比传统的处理是12-13分贝。
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Multistage algorithms for extended dwell target detection
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.
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