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

机译:基于具有两个互质频率的超稀疏嵌套MIMO阵列的DOA估计

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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.
机译:本文主要通过在两个互质频率上操作,来解决超稀疏嵌套(USN)MIMO阵列的到达方向(DOA)估计问题。 USN MIMO阵列由一个稀疏均匀(SU)发送阵列和一个具有嵌套关系的更多SU接收阵列组成,后者生成一个SU sum协阵列。在这种情况下,DOA估计是混叠的,因为对于参考操作频率,USN MIMO阵列的和协阵列(DCSC)的差协阵列也是SU。为了消除混叠,利用具有互质关系的附加工作频率来形成额外的SU sum协阵列,其中两个相邻虚拟传感器的间隔与参考频率(RF)的互质为互质。结果,求和协阵列的两个互素间隔被组合成一个互素和协阵列,该互素和协阵列提供具有大部分连续虚拟传感器的期望DCSC。最后,对于这些连续的虚拟DCSC传感器,获得具有连续相关滞后的增强相关矩阵以计算MUSIC频谱。仿真结果表明,与物理传感器相比,更多目标具有可分辨的能力,并且在比例和非比例目标光谱情况下的性能比较。

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