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Non-circular signals for nested array: sum–difference co-array and direction of arrival estimation algorithm

机译:嵌套数组的非圆形信号:求和差协数组和到达方向估计算法

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摘要

Nested array has aroused remarkable attention due to the capability to obtain both enhanced degrees of freedom (DOFs) and enlarged array aperture, whereas only difference co-array is employed. Here, the authors construct the sum co-array of nested array by utilising the non-circular (NC) characteristic and, subsequently, the sum-difference (SD) co-array is obtained by careful crafting of the sum co-array and the typical difference co-array, which doubles the resulting co-array aperture and, simultaneously, further increases the achievable DOF compared with the difference co-array of nested array. Moreover, to circumvent the time-consuming two-dimensional spectral search, the authors proposed the reduced-dimension multiple signals classification (MUSIC) algorithm with the SD (SD-RD-MUSIC) co-array of the nested array by discarding the NC phase. Resultantly, the proposed SD-RD-MUSIC co-array algorithm can resolve more signals and obtain more accurate direction of arrival estimates. In addition, the effectiveness and superiority of the proposed method are validated by numerical simulations.
机译:嵌套阵列由于能够获得增强的自由度(DOF)和增大的阵列孔径而引起了极大的关注,而仅采用了差分协同阵列。在这里,作者利用非圆形(NC)特性构造嵌套数组的和协数组,随后,通过精心设计和协和数组并获得和差(SD)协数组。与嵌套阵列的差分协同阵列相比,典型的差分协同阵列可以使所得的协同阵列孔径加倍,同时还可以提高可实现的自由度。此外,为了避免费时的二维频谱搜索,作者通过丢弃NC相位与嵌套阵列的SD(SD-RD-MUSIC)协阵列一起提出了降维多信号分类(MUSIC)算法。结果,所提出的SD-RD-MUSIC共阵列算法可以解析更多的信号并获得更准确的到达方向估计。另外,通过数值仿真验证了该方法的有效性和优越性。

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