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Signal and noise subspace decomposition for a linear antenna array using SVD

机译:使用SVD的线性天线阵列的信号和噪声子空间分解

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In the vast majority of signal processing applications, the signal is intended to be analyzed to obtain a variety of data from the signal. It is decomposed into signal subspaces to perform this analysis. The noise in the signal during analysis is undesirable. If the signal incoming to an antenna array contains noise, it should be filtered before processing signal. In this study, we have tried to divide the uniform linear antenna array into subspaces of incoming signals from multiple signal sources with various frequencies, noise and arrival angles. The Singular Value Decomposition (SVD) method is used to separate the signal subspace and noise subspace. According to the singular values obtained, the information about the frequencies of the signals and whether the signal contains noise. Also, the number of sources can be estimated by means of singular values.
机译:在绝大多数信号处理应用中,打算对信号进行分析,以从信号中获取各种数据。将其分解为信号子空间以执行此分析。分析期间信号中的噪声是不希望的。如果进入天线阵列的信号包含噪声,则应在处理信号之前对其进行滤波。在这项研究中,我们试图将均匀线性天线阵列划分为来自多个信号源的输入信号的子空间,这些信号源具有不同的频率,噪声和到达角度。奇异值分解(SVD)方法用于分隔信号子空间和噪声子空间。根据获得的奇异值,获得有关信号频率以及信号是否包含噪声的信息。同样,可以通过奇异值来估计源的数量。

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