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A novel method in compensating random perturbations in eigen-based subspace method

机译:基于eIGen的子空间方法中随机扰动的一种新方法

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The problem of random perturbations as induced by the nonstationary nature of the emitting sources and the sensing environment in direction-of-arrival (DOA) determination by sensor array is considered. Focus has been made on the effect of these random perturbations on the covariance matrix as generated by the sensor data. Based on certain assumptions, we show that the perturbed covariance matrix can be expressed as the Schur-Hadamard product between the ideal one and a perturbation matrix which is independent of both the DOAs and the source covariance. However, unlike the MLE and exhaustive search approach used to determine the DOAs, we propose a fast, simple and robust method to compensate for the random perturbations. Simulations on MUSIC with different models of perturbation distributions are carried out and promising results are obtained.
机译:考虑了由传感器阵列的发射源的非间断性质和感测环境引起的随机扰动的问题。 已经对传感器数据产生的这些随机扰动的效果进行了焦点。 基于某些假设,我们表明,扰动的协方差矩阵可以表示为理想的一个和扰动矩阵之间的施塔拉德产品,其与DOA和源协方差无关。 然而,与用于确定DOAS的MLE和详尽的搜索方法不同,我们提出了一种快速,简单且坚固的方法来补偿随机扰动。 对具有不同模型的扰动分布模型进行仿真,并获得了有希望的结果。

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