DOA Estimation Based on Ultra Sparse Nested MIMO Array with Two Co-prime Frequencies

Tianyao Long, Yong Jia, Li Jiang, Binge Yan, Tanzheng Yang
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Abstract

This paper mainly deals with the problem of direction-of-arrival (DOA) estimation for the ultra sparse nested (USN) MIMO array by operating on two co-prime frequencies. The USN MIMO array consists of a sparse uniform (SU) transmitting array and a more SU receiving array with nested relationship, which generates a SU sum coarray. In this case, the DOA estimation is aliasing because the difference coarray of the sum coarray (DCSC) of the USN MIMO array is also SU for the reference operation frequency. To remove the aliasing, an additional operation frequency with co-prime relationship is utilized to form an extra SU sum coarray where the spacing of two adjacent virtual sensors is co-prime with that of reference frequency(RF). As a result, two co-prime spacings of sum coarrays are combined into a co-prime sum coarray which provides a desired DCSC with a majority of contiguous virtual sensors. Finally, with respect to these contiguous virtual DCSC sensors, an augmented correlation matrix with contiguous correlation lags is obtained to calculate MUSIC spectrum. Simulation results demonstrate the resolvable ability for more targets than physical sensors and the performance comparison under both cases of proportional and non-propotional target spectra.
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基于两同素频率超稀疏嵌套MIMO阵列的DOA估计
本文主要研究了超稀疏嵌套MIMO (USN)阵列在两个共素频率下的到达方向估计问题。USN MIMO阵列由一个稀疏均匀(SU)发射阵列和一个更稀疏均匀(SU)的嵌套关系接收阵列组成,形成一个SU和共阵。在这种情况下,由于USN MIMO阵列的和阵(DCSC)的差阵对于参考工作频率也是SU,因此DOA估计会混叠。为了消除混叠,利用一个具有协素数关系的额外工作频率形成一个额外的SU和共阵,其中相邻两个虚拟传感器的间距与参考频率(RF)的间距为协素数。因此,将两个共素和阵组合成一个共素和阵,该共素和阵提供了具有大多数相邻虚拟传感器的理想DCSC。最后,针对这些连续的虚拟DCSC传感器,得到具有连续相关滞后的增广相关矩阵来计算MUSIC频谱。仿真结果表明了该传感器比物理传感器对更多目标的可分辨能力,并对比例和非比例目标光谱进行了性能比较。
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