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Joint calibration of array shape and sensor gain/phase for highly deformed arrays using wideband signals

机译:使用宽带信号对高度变形的阵列进行阵列形状和传感器增益/相位的联合校准

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A joint sensor position and gain/phase calibration method for highly deformed arrays is proposed. It applies to the case where the sensor gain is omnidirectional and frequency-invariant, and the sensor phase is directional and frequency-invariant. The method is initialized with the raw estimates of the sensor gains, which are simply obtained from the main diagonal elements of the sample covariance matrix. Then, it alternately updates either the sensor gain estimates or the sensor position and phase estimates while fixing the other. When the sensor gain estimates are available, the steering matrices for all the frequency bins are estimated using the constant modulus method. By combining all these steering matrices, the estimates of the sensor positions and the frequency-invariant sensor phases are straightforwardly derived. Then, the sensor gain estimates are refined for the next iteration by using the orthogonality of the subspaces. To resolve the phase ambiguities due to the large position mismatches of highly deformed arrays, the nominal intersensor distance and the array bending angle are used. The Cramer-Rao lower bounds (CRLBs) for the unknown sensor gain/phase and position are also derived. The performance of the proposed method is evaluated using simulation data and compared with the CRLBs. (C) 2019 Elsevier B.V. All rights reserved.
机译:提出了一种用于高变形阵列的联合传感器位置和增益/相位校准方法。它适用于传感器增益为全向且频率不变且传感器相位为方向且频率不变的情况。该方法用传感器增益的原始估计值初始化,该估计值可以简单地从样本协方差矩阵的主要对角元素中获得。然后,它交替更新传感器增益估计值或传感器位置和相位估计值,同时确定另一个。当传感器增益估计可用时,将使用恒定模量方法来估计所有频率仓的转向矩阵。通过组合所有这些控制矩阵,可以直接得出传感器位置和频率不变传感器相位的估计值。然后,通过使用子空间的正交性,为下一次迭代优化传感器增益估计。为了解决由于高度变形的阵列的较大位置失配而引起的相位模糊性,使用标称传感器间距离和阵列弯曲角度。还得出未知传感器增益/相位和位置的Cramer-Rao下限(CRLB)。使用仿真数据评估了所提出方法的性能,并与CRLB进行了比较。 (C)2019 Elsevier B.V.保留所有权利。

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