Recently, dilated nested arrays have been proposed on a moving platform to increase the uniform degrees of freedom (uDOF) by a factor of three by exploiting array motion. However, no literature addresses the issue whether the same dilation method still performs well for other array geometries such as coprime arrays, augmented nested arrays and minimum redundancy arrays. Compared with nested arrays, these arrays either achieve higher uDOF or exhibit more robustness to mutual coupling among sensors. In this paper, we propose a novel sparse array geometry named dilated arrays (DAs) on a moving platform by applying the dilation method to other array geometries. First, by exploiting the relationship between the element positions in the difference coarrays of the original linear array and the synthetic array after motion, we prove that, for a DA on a moving platform, the maximum uDOF can be tripled compared to that of its original array regardless of the array geometry. Therefore, the number of sources that can be resolved for direction-of-arrival (DOA) estimation is increased threefold. Second, we prove that a DA reduces mutual coupling compared with its original array. As a result, the DA is more robust to mutual coupling than its original array. Third, we extend one-dimensional DAs to the two-dimensional (2-D) case, yielding a new 2-D sparse array geometry named two-parallel DAs. We show that by exploiting array motion, two-parallel DAs can increase the number of detectable sources threefold. Numerical simulations demonstrate the superior performance of the proposed array geometries.

中文翻译：

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膨胀阵列：移动平台上增加均匀自由度并减少互耦的稀疏阵列系列


最近，有人提出在移动平台上使用膨胀嵌套阵列，通过利用阵列运动将均匀自由度 (uDOF) 增加三倍。然而，没有文献解决相同的膨胀方法对于其他阵列几何形状（例如互质阵列、增强嵌套阵列和最小冗余阵列）是否仍然表现良好的问题。与嵌套阵列相比，这些阵列要么实现更高的 uDOF，要么对传感器之间的相互耦合表现出更强的鲁棒性。在本文中，我们通过将扩张方法应用于其他阵列几何形状，提出了一种新颖的稀疏阵列几何形状，称为移动平台上的扩张阵列（DA）。首先，通过利用原始线性阵列和运动后合成阵列的差异协同阵列中元素位置之间的关系，我们证明，对于移动平台上的DA，最大uDOF可以比原始线性阵列增加三倍数组，与数组几何形状无关。因此，可用于波达方向 (DOA) 估计的源数量增加了三倍。其次，我们证明 DA 与其原始阵列相比减少了互耦合。因此，DA 比其原始阵列更能抵抗相互耦合。第三，我们将一维 DA 扩展到二维 (2-D) 情况，产生一种新的 2-D 稀疏数组几何结构，称为两并行 DA。我们证明，通过利用阵列运动，两个并行 DA 可以将可检测源的数量增加三倍。数值模拟证明了所提出的阵列几何形状的优越性能。