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On the algebraic identification of the frequencies, amplitudes and phases of two sinusoidal signals from their noisy sum

机译:关于两个正弦信号的噪声,总和的频率,幅度和相位的代数识别

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摘要

An algebraic identification approach is used for the fast and reliable on-line determination of the defining parameters of two sinusoidal signals of different, unknown, amplitudes, phases and frequencies from their noise-perturbed measured sum. The proposed method is based on the algebraic derivative approach, defined in the frequency domain, yielding exact calculation formulae for the unknown parameters when interpreted in a noise-free time-domain environment. The proposed computation formulae are synthesized in terms of time-varying linear, unstable, filters in combination with classical low-pass filters. The proposed algorithms are insensitive to initial conditions, require no special design parameter tuning and the fast convergence is of non-asymptotic nature. The on-line computations are performed in a time interval which is only a fraction of the first full cycle of one of the integrating components of the measured signal. Several simulations are shown to verify the algorithm proposed. Finally, experimental results dealing with actual laboratory signals are presented.
机译:代数识别方法用于快速可靠地在线确定两个正弦信号的定义参数,这两个正弦信号的振幅,相位和频率来自其噪声扰动的测量总和。所提出的方法基于在频域中定义的代数导数方法,当在无噪声的时域环境中进行解释时,可为未知参数得出精确的计算公式。所提出的计算公式是根据时变线性,不稳定滤波器与经典低通滤波器组合而成的。所提出的算法对初始条件不敏感,不需要特殊的设计参数调整,并且快速收敛具有非渐近性。在线计算是在一个时间间隔中执行的,该时间间隔只是被测信号的一个积分分量的第一个完整周期的一部分。显示了几个仿真结果,以验证所提出的算法。最后,介绍了处理实际实验室信号的实验结果。

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