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A Method of Target Identification with UWB Based on S-Transform and Improved Artificial Bee Colony Algorithm

机译:基于S变换和改进人工蜂群算法的超宽带目标识别方法

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Ultra-wideband signal (UWB) has been used in communication, location, and identification. In this paper, a novel target identification method is proposed. The UWB received signals is processed by time-frequency analysis method: S-transform. S-transform is an extension of short time Fourier transform and continuous wavelet transform, and it has good time-frequency characteristics. Then we use improved artificial bee colony (ABC) algorithm to optimize the penalty factor and kernel parameter of support vector machine (SVM), and finish the target identification. In view of the basic artificial bee colony algorithm has the problem of slow convergence speed. We propose a probability selection method based on quadratic function to optimize the algorithm.
机译:超宽带信号(UWB)已用于通信,定位和识别。本文提出了一种新的目标识别方法。 UWB接收信号通过时频分析方法:S变换进行处理。 S变换是短时傅立叶变换和连续小波变换的扩展,具有良好的时频特性。然后使用改进的人工蜂群算法(ABC)对惩罚因子和支持向量机(SVM)的核参数进行优化,完成目标识别。鉴于基本的人工蜂群算法具有收敛速度慢的问题。我们提出了一种基于二次函数的概率选择方法来优化算法。

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