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Radar target recognition using one-dimensional evolutionary programming-based clean

机译:基于一维进化规划的干净目标雷达目标识别

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In this work, we present a method for radar target recognition using an one-dimensional (1-D) evolutionary programming-based CLEAN. This I-D scattering center extraction method relies upon evolutionary programming and an undamped exponential model. It is accurate, robust and fast. Moreover, it is free from the resolution problems that arise in FFT-based CLEAN. Unlike with model-based techniques, the accuracy of extracted parameters is unaffected by false estimation of the number of scattering centers. Experimental results show that the 1-D evolutionary programming-based CLEAN algorithm can be successfully applied to radar target recognition with correlation-based approaches to reduce data storage, as well as with neural network-based approaches to efficiently extract feature vectors. [References: 25]
机译:在这项工作中,我们提出了一种基于一维(1-D)进化编程的CLEAN的雷达目标识别方法。这种I-D散射中心提取方法依赖于进化规划和无阻尼指数模型。它准确,可靠且快速。而且,它没有基于FFT的CLEAN中出现的分辨率问题。与基于模型的技术不同,提取参数的准确性不受散射中心数量错误估计的影响。实验结果表明,基于一维进化规划的CLEAN算法可以成功地应用于雷达目标识别,其基于相关的方法可以减少数据存储,而基于神经网络的方法可以有效地提取特征向量。 [参考:25]

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