基于大规模虚拟阵列数据的DoA估计

Hung-Anh Nguyen, Kim Mahler, M. Peter, W. Keusgen, Taro Eichler, Heinz Mellein
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引用次数: 7

摘要

本文介绍了一种从宽带信道测量数据中获取传播路径方向信息的新方法,特别是关于未来在毫米波波段的测量。该方法基于对空间采样信道的大规模虚拟阵列分析。例如,用全向天线进行测量可以获得相应的数据,全向天线在测量过程中是连续移动的。将大规模估计方法与一种著名的平滑MUSIC算法进行了比较。该方法在大尺度下产生了相当稳定的DoA估计,而基于小尺度的MUSIC算法由于衰落效应而表现出较高的方差。然而,为了提高doa的精度,并评估结果对输入参数的依赖性,所提出的方法还需要进一步的评估。
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Estimation of DoA based on large-scale virtual array data
In this paper a new method has been introduced to obtain directional information on the propagation paths from wide-band channel measurement data, in particular with respect to future measurements in the mm-wave band. The method is based on large-scale virtual array analysis of the spatially sampled channel. Corresponding data can e.g. be obtained by measurements with an omnidirectional antenna, which is continuously moved during the measurement. The large-scale estimation approach has been compared with a well-known method, the smooth MUSIC algorithm. The proposed method yields quite stable DoA estimations on a large scale, whereas the small-scale-based MUSIC algorithm shows a high variance because of fading effects. However, the method proposed needs to be further evaluated in order to improve the accuracy of DoAs and to assess the dependence of the results on the input parameters.
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