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An adaptive sampling algorithm for the efficient prediction of antenna radiation patterns over a wide frequency bandwidth

机译:一种自适应采样算法,用于在宽频带宽上有效预测天线辐射图案

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We present a robust method to predict full radiation patterns over a large frequency bandwidth using the knowledge of the pattern at a few frequency points. The frequency points are selected adaptively such that a set of linearly independent basis functions, called characteristic basis function patterns (CBFPs), is obtained. The model consists of a linear combination of CBFPs where expansion coefficients are parameterized with respect to frequency and interpolated to accurately yield the radiation pattern at a desired frequency within the bandwidth of interest. The method has a built-in absolute error control, given by the ratio of the smallest and largest singular values of the column-stacked matrix of CBPFs, providing a trade-off between accuracy and complexity of the model. The proposed method is validated through illustrative examples.
机译:我们介绍了一种稳健的方法,用于使用少数频率点的知识来预测大频率带宽上的完全辐射模式。获得频率点,自适应地选择,使得获得了一组被称为特征基函数模式(CBFP)的线性独立的基函数。该模型包括CBFP的线性组合,其中相对于频率参数化膨胀系数并内插,以精确地在感兴趣的带宽内以所需的频率屈服的辐射图案。该方法具有内置的绝对错误控制,由CBPFS列堆叠矩阵的最小和最大奇异值的比率给出,在模型的精度和复杂性之间提供权衡。通过说明性示例验证所提出的方法。

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