2) uncorrelated sources with N phys'/> Sparse Fractal Array Design with Increased Degrees of Freedom
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Sparse Fractal Array Design with Increased Degrees of Freedom

机译:自由度提高的稀疏分形阵列设计

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Sparse arrays are of great interest since they can identify O(N2) uncorrelated sources with N physical sensors. This stems from their large difference coarray, defined as the differences between sensor locations. In a recent study, desired array properties such as closed-form expression for sensor locations, symmetry and large hole-free difference coarray were considered and it was shown that most existing sparse arrays do not exhibit these characteristics simultaneously. Standard Cantor arrays were shown to satisfy all the criteria above, however, their difference coarrays are of size O(Nlog2 3) which is smaller than that obtained with minimum redundancy arrays and nested arrays. In this paper, we introduce a fractal array design where a generator array is extended in a simple recursive fashion. In contrast to previous work, the generator is assumed to be a sparse array with a hole-free difference coarray. We study the resulting arrays and prove they inherit their properties from the generator. Thus, this approach can be used to extend any known sparse configuration to an arbitrarily large array. A small-scale array, which meets all design criteria, can be created and then expanded to generate a symmetric fractal array with a difference coarray of size O(N2), unlike Cantor arrays.
机译:稀疏阵列非常有用,因为它们可以识别O(N 2 )具有N个物理传感器的不相关来源。这源于它们的大差异共阵列,即传感器位置之间的差异。在最近的一项研究中,考虑了所需的阵列属性,例如传感器位置的封闭式表达,对称性和大无孔差协阵列,并且表明大多数现有的稀疏阵列不能同时显示这些特征。显示标准Cantor数组满足上述所有条件,但是,它们的差协数组大小为O(N log2 3 )小于使用最小冗余数组和嵌套数组所获得的值。在本文中,我们介绍了一种分形数组设计,其中生成器数组以简单的递归方式扩展。与以前的工作相反,生成器被假定为具有无孔差协数组的稀疏数组。我们研究了结果数组,并证明它们从生成器继承了它们的属性。因此,该方法可用于将任何已知的稀疏配置扩展到任意大的阵列。可以创建一个满足所有设计标准的小规模阵列,然后进行扩展以生成对称分形阵列,该对称分形阵列具有大小为O(N2)的差分协阵列,这与Cantor阵列不同。

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