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Array calibration with modified Iterative HOS-SOS (MIHOSS) algorithm

机译:使用改进的迭代式HOS-SOS(MIHOSS)算法进行阵列校准

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Joint direction-of-arrival (DOA) and sensor position estimation for randomly deployed sensors is introduced in Iterative HOS-SOS (IHOSS) algorithm [1]. IHOSS algorithm exploits the advantages of both higher-order-statistics (HOS) and second-order-statistics (SOS) with an iterative algorithm using two reference sensors. The iterative algorithm is guaranteed to converge. IHOSS algorithm solves the position ambiguity by using source signals observed at multiple frequencies and hence it is applicable for wideband signals. In this paper, we propose Modified-IHOSS (MIHOSS) algorithm to solve the same problem for narrowband signals. In MIHOSS, it is assumed that the nominal sensor positions are known. It is shown that ambiguity problem is solved effectively without any assumption on the position perturbations. The upper bound of perturbations for unambiguous sensor position estimation is presented. The performance of MIHOSS approaches to the Cramér-Rao bound (CRB) for both DOA and position estimation.
机译:迭代部署的HOS-SOS(IHOSS)算法[1]中引入了随机部署传感器的联合到达方向(DOA)和传感器位置估计。 IHOSS算法利用使用两个参考传感器的迭代算法,充分利用了高阶统计量(HOS)和二阶统计量(SOS)的优势。保证迭代算法收敛。 IHOSS算法通过使用在多个频率处观察到的源信号解决了位置歧义,因此适用于宽带信号。在本文中,我们提出了改进的IHOSS(MIHOSS)算法来解决窄带信号的相同问题。在MIHOSS中,假定传感器的标称位置是已知的。结果表明,无需对位置扰动进行任何假设,就可以有效地解决歧义问题。给出了用于明确传感器位置估计的摄动上限。对于DOA和位置估计,MIHOSS的性能均接近Cramér-Rao界(CRB)。

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