传感器阵列的多尺度自校准
Multisource Self-calibration for Sensor Arrays
摘要：
如果天线具有方向相关增益并且同时存在多个校准器源，则传感器阵列的校准更加复杂。我们研究这种情况下的任意几何形状的传感器阵列，但相同的元素，即具有相同的方向相关的增益模式的元素。一个加权交替最小二乘（WALS）算法推导出迭代求解的方向无关的复杂的阵列元件的增益，它们的噪声功率和校准源的方向上的增益。该问题的延伸是表观校准源位置未知的情况，例如，这是由于折射传播路径。对于这种情况下，WALS方法补充加权子空间拟合（WSF）方向发现技术。使用蒙特卡罗模拟，我们证明了这两种方法是渐近统计有效的，即使在低信噪比的情况下，在两个迭代收敛。
英文摘要：
Calibration of a sensor array is more involved if the antennas have direction dependent gains and multiple calibrator sources are simultaneously present. We study this case for a sensor array with arbitrary geometry but identical elements, i.e. elements with the same direction dependent gain pattern. A weighted alternating least squares (WALS) algorithm is derived that iteratively solves for the direction independent complex gains of the array elements, their noise powers and their gains in the direction of the calibrator sources. An extension of the problem is the case where the apparent calibrator source locations are unknown, e.g., due to refractive propagation paths. For this case, the WALS method is supplemented with weighted subspace fitting (WSF) direction finding techniques. Using Monte Carlo simulations we demonstrate that both methods are asymptotically statistically efficient and converge within two iterations even in cases of low SNR.
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