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3M relationship pattern for detection and estimation of unknown frequencies for unknown number of sinusoids based on eigenspace analysis of Hankel matrix

机译:基于汉克尔矩阵特征空间分析的3M关系模式,用于未知数目的正弦波的未知频率的检测和估计

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We develop a novel approach to estimate the n unknown constituent frequencies of a sinusoidal signal that comprises of unknown number, n, of sinusoids of unknown phases and unknown amplitudes. The approach has been applied to multiple sinusoidal signals in the presence of white Gaussian noise with varying signal to noise ratio (SNR). The approach is based on eigenspace analysis of Hankel matrix formed with the samples from averaged frequency spectrum of the signal obtained through multiple measurements. The eigenspace analysis is based on the newly developed 3M relationship which reflects and exploits the relationship between the consecutive sets of Maximum, Middle and Minimum eigenvalues of square symmetric matrix of the Hankel matrix. The 3M relationship exhibits a pattern in line with the order of the Hankel matrix and leads to parametric estimation of the constituent sinusoids. This paper also presents the relationship equation between the size of 3M relationship pattern and the dimensions of the Hankel matrix. The performance of the developed approach has been tested to correctly estimate multiple constituent frequencies within a noisy signal.
机译:我们开发了一种新颖的方法来估计正弦信号的n个未知组成频率,该信号包含未知数量n个未知相位和幅度的正弦信号。该方法已应用于存在白色高斯噪声且信噪比(SNR)变化的多个正弦信号。该方法基于汉克矩阵的本征空间分析,该汉克矩阵是通过多次测量获得的信号平均频谱中的样本形成的。特征空间分析基于新开发的3M关系,该关系反映并利用了汉克尔矩阵的方形对称矩阵的最大,中和最小特征值的连续集合之间的关系。 3M关系表现出与Hankel矩阵的顺序一致的模式,并导致对正弦曲线的参数估计。本文还提出了3M关系模式的大小与Hankel矩阵的维数之间的关系方程。已对所开发方法的性能进行了测试,可以正确估计噪声信号中的多个组成频率。

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