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A maneuvering target detection in time-series Doppler spectrums with self-organizing model

机译:具有自组织模型的时间序列多普勒频谱中的机动目标检测

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This paper presents a probability of detection enhancement technique for a maneuvering target with a low radar cross section in time-series Doppler spectrums. The target signal and a noise variance are estimated by the self-organizing model applied to the particle filter and the history of the particle information is used for the detection with a constant false alarm rate. A Monte Carlo simulation is carried out for the performance investigation. The results show that the probability is enhanced, even when a target has a high angular velocity.
机译:本文提出了一种在时间序列多普勒频谱中具有低雷达横截面的机动目标的检测增强技术的可能性。目标信号和噪声方差由应用于粒子滤波器的自组织模型估算,并且粒子信息的历史记录用于以恒定误报率进行检测。进行性能研究的蒙特卡洛模拟。结果表明,即使目标具有高角速度,该概率也会增加。

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