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Unequally-excited linear totally random antenna arrays for multi-beam patterns

机译:多波束方向图的不等激励线性完全随机天线阵列

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Linear random antenna arrays are usually studied in conjunction with uniform excitations with, at most, a linear phase shift in order to steer the main beam. This offers some advantages in terms of the feeding network but puts limitations on the array factor that can be obtained. The authors introduce unequally excited random arrays whose excitation currents are obtained by suitable transformations of the random variables related to the element positions. Besides, the first- and second-order statistic characterisation, the uniform norm (i.e. the supremum) of difference between the mean (the desired one) and the actual array factors is estimated. In particular, while in the general case, this is achieved only via a Monte Carlo study, for the case of symmetric arrays (where the elements are randomly deployed symmetrically with respect to the array aperture centre) that norm is analytically estimated using the up-crossing theory for random processes. It is shown that the proposed unequally excited random arrays, unlike some other previous approaches, allow shaping the mean radiation pattern. However, the procedure in general yields reduced achievable performance. Therefore, the theoretical findings are checked through some numerical examples only for the important class of multi-beam array factors.
机译:通常将线性随机天线阵列与至多具有线性相移的均匀激励一起研究,以操纵主波束。就馈电网络而言,这提供了一些优势,但对可获得的阵列因子施加了限制。作者介绍了不等激发的随机阵列,其激发电流是通过对与元素位置有关的随机变量进行适当转换而获得的。此外,估算一阶和二阶统计量,还可以估算出平均值(期望值)与实际数组因子之差的统一范数(即最高)。特别是,在一般情况下,这只能通过蒙特卡洛研究来实现,对于对称阵列(其中元素相对于阵列孔径中心对称地随机部署)的情况,使用随机过程的交叉理论。结果表明,与其他一些先前的方法不同,所提出的不等激发随机阵列允许对平均辐射方向图进行整形。但是,该程序通常会降低可实现的性能。因此,仅通过重要的多束阵列因子类别的数值例子来检验理论发现。

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