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Compressive sensing based target detection in delay-doppler radars [Sikiştirilmiş algilama ile darbe-doppler radar hedef tespiti]

机译:延迟多普勒雷达中基于压缩感知的目标检测[压缩感知的脉冲多普勒雷达目​​标检测]

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摘要

Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due to its nature, is one of the important application of CS theory. Even if CS approach is suitable for radar systems, classical detections schemes under Neyman-Pearson formulations may result high probability of false alarm, when CS approach is used, especially if the target has off-grid parameters. In this study, a new detection scheme which enables CS techniques to be used in radar systems is investigated. © 2013 IEEE.
机译:压缩感测理论表明,可以从其次奈奎斯特速率随机样本中重建稀疏信号。凭借此属性,CS方法具有许多应用程序。雷达系统由于其性质而处理稀疏信号,是CS理论的重要应用之一。即使CS方法适用于雷达系统,当使用CS方法时,尤其是在目标具有离网参数的情况下,采用Neyman-Pearson公式表示的经典检测方案也可能会导致误报的可能性很高。在这项研究中,研究了一种可使CS技术用于雷达系统的新检测方案。 ©2013 IEEE。

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