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Constrained least squares estimation of sinusoidal frequencies and application to fast estimation of very low frequency tones

机译:正弦频率的约束最小二乘估计及其在极低频音的快速估计中的应用

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We consider the problem of least squares estimation of the frequency of a single noiseless sinusoidal signal. By constraining the signal model to be an oscillatory system and derive least squares algorithm to estimate the frequency parameters. We extend the solution to the general case of multiple noiseless sinusoids and express the global solution in terms of the inverse of a Toeplitz plus Hankel matrix. We then apply the above algorithm for ultra fast estimation of the frequency of a very low frequency sine wave. Such problems arise in the digital implementations of Ring Tone detectors in automated telephony systems. In high SNR environments, we are able to obtain reasonable estimates of the frequency within a fraction of a single period of the sine wave. We derive expressions for the bias due to additive noise and also experimentally examine the effects of signal distortions.
机译:我们考虑对单个无噪声正弦信号的频率进行最小二乘估计的问题。通过将信号模型约束为一个振荡系统,并推导最小二乘算法来估计频率参数。我们将解扩展到多个无噪声正弦波的一般情况,并以Toeplitz加Hankel矩阵的逆表示整体解。然后,我们将上述算法用于超快速估计非常低频正弦波的频率。这样的问题出现在自动电话系统中的铃音检测器的数字实现中。在高SNR环境中,我们能够在正弦波单个周期的一小部分内获得合理的频率估计。我们推导了由于加性噪声引起的偏差的表达式,并通过实验检查了信号失真的影响。

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