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DOA and Phase Error Estimation for a Partly Calibrated Array With Arbitrary Geometry

机译:具有任意几何的部分校准阵列的DOA和相位误差估计

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This paper presents a novel strategy to simultaneously estimate the direction of arrival (DOA) of a source signal and the phase error of a partly calibrated array with arbitrary geometry. We add up the snapshot data of two different sensors, and then extract a knowledge associated with the DOA and phase errors of these two elements by using singular value decomposition. In such a manner, we can establish a series of linear equations with respect to the unknown DOA and phase error, by simply conducting the procedure on any two sensor elements. On this basis, it can be shown that the problem of jointly estimating DOA and phase error is equivalent to a least square (LS) problem with a quadratic equality constraint. To solve this LS problem (so that the DOA and phase error can be obtained), an effective convex-concave procedure is employed. Different from the conventional algorithms that are limited to specific array geometries, the proposed one is suitable for arrays with arbitrary geometries. More importantly, the devised method only requires one extra calibrated sensor, which is not necessarily adjacently located with the reference one. Several simulations are carried out in this paper and the effectiveness of the devised method can be clearly observed.
机译:本文呈现了一种新的策略,以便同时估计源信号的到达方向(DOA)以及具有任意几何的部分校准阵列的相位误差。我们添加了两个不同传感器的快照数据,然后通过使用奇异值分解来提取与这两个元素的DOA和相位误差相关联的知识。以这种方式,通过简单地在任何两个传感器元件上进行过程,我们可以相对于未知的DOA和相位误差建立一系列线性方程。在此基础上,可以示出共同估计DOA和相位误差的问题等同于具有二次平等约束的最小二乘(LS)问题。为了解决这个LS问题(使得可以获得DOA和相位误差),采用有效的凸凹过程。与限定对特定阵列几何形状的传​​统算法不同,所提出的算法适用于具有任意几何形状的阵列。更重要的是,设计的方法仅需要一个额外的校准传感器,这不一定与参考值相邻。本文进行了几种模拟,可以清楚地观察到设计方法的有效性。

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