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Decoupled 2D Direction of Arrival Estimation Using Compact Uniform Circular Arrays in the Presence of Elevation-Dependent Mutual Coupling

机译:存在高度依赖的相互耦合时,使用紧凑均匀圆形阵列解耦二维到达方向的估计

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Based on the rank reduction theory (RARE), a decoupled method for 2D direction of arrival (DOA) estimation in the presence of elevation-dependent mutual coupling is proposed for compact uniform circular arrays (UCAs). Using a new formulation of the beamspace array manifold in the presence of mutual coupling, the azimuth estimates are decoupled from the elevation estimates and obtained with no need for the exact knowledge of mutual coupling. For the elevation estimation, a 1D parameter search in the elevation space for every azimuth estimate is performed with the elevation-dependent mutual coupling effect compensated efficiently. Though the computational load for the elevation estimation is increased compared to that of the original UCA-RARE algorithm, the 1D parameter search in our method overcomes most of the inherent shortcomings of the UCA-RARE algorithm. This enables unambiguous and paired 2D DOA estimation with the elevation-dependent mutual coupling effect being compensated for effectively. Numerical examples are presented to demonstrate the effectiveness of the proposed method.
机译:基于秩减少理论(RARE),提出了一种用于紧凑均匀圆形阵列(UCA)的,与海拔相关的相互耦合的二维到达方向(DOA)估计的解耦方法。在存在相互耦合的情况下,使用束空间阵列歧管的新公式,方位角估计值与高程估计值解耦,并且不需要相互耦合的确切知识即可获得方位角估计值。对于高程估计,在高程空间中针对每个方位角估计执行一维参数搜索,并有效补偿与高程相关的互耦合效应。尽管与原始UCA-RARE算法相比,高程估算的计算量有所增加,但我们方法中的一维参数搜索克服了UCA-RARE算法的大多数固有缺点。这样就可以进行明确且成对的2D DOA估计,并且可以有效补偿与仰角相关的互耦效应。数值算例表明了该方法的有效性。

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