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Selection of dimensional normalization parameter in digital computation of the fractional Fourier Transform

机译:分数阶傅里叶变换数字计算中尺寸归一化参数的选择

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In the digital computation of the fractional Fourier Transform, the dimensional normalization is needed. The initial frequency and chirp rate of a chirp signal are changed by the dimensional normalization parameter, and the position of the chirp signal's peak on the two-dimensional parameter (p, u) plane is also changed. This influences the detection of the multi-component chirp signals. In order to decrease the influence, a method is presented to choose the dimensional normalization parameter, based on the distance between two chirp signals' peaks. First, the coordinates of the chirp signal's peak is educed on the (p, u) plane. And the relationships between the dimensional normalization parameter and the distances between two chirp signals' peaks on p axis and on u axis are analyzed. It is discovered that the distances varies with the dimensional normalization parameter and they both have their own maximums. By changing signals' observation time and sampling frequency, selecting a reasonable dimensional normalization parameter can increase the distances between two signals' peaks. It can improve multi-component chirp signals' resolution ability and reduce the shading effect between strong signals and weak signals. The effectiveness of the method is verified by the computer simulations.
机译:在分数阶傅立叶变换的数字计算中,需要尺寸归一化。线性调频信号的初始频率和线性调频率通过维数归一化参数进行更改,并且线性调频信号的峰值在二维参数(p,u)平面上的位置也将发生变化。这影响了多分量线性调频信号的检测。为了减小影响,提出了一种基于两个线性调频信号峰值之间的距离选择尺寸归一化参数的方法。首先,在(p,u)平面上得出线性调频脉冲信号峰值的坐标。分析了尺寸归一化参数与两个线性调频脉冲峰值在p轴和u轴上的距离之间的关系。发现距离随尺寸归一化参数而变化,并且它们都有自己的最大值。通过更改信号的观察时间和采样频率,选择合理的尺寸归一化参数可以增加两个信号峰值之间的距离。它可以提高多分量线性调频信号的分辨能力,并减小强信号和弱信号之间的阴影效应。通过计算机仿真验证了该方法的有效性。

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