正弦频率的约束最小二乘估计及其在极低频音调快速估计中的应用

P. Chitrapu, Z. Pan
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引用次数: 3

摘要

研究了单个无噪声正弦信号频率的最小二乘估计问题。通过将信号模型约束为振荡系统,推导出最小二乘算法来估计频率参数。我们将解推广到多个无噪声正弦波的一般情况,并用Toeplitz + Hankel矩阵的逆表示全局解。然后,我们应用上述算法对极低频正弦波的频率进行超快速估计。这类问题出现在自动电话系统中铃声检测器的数字实现中。在高信噪比环境中,我们能够在正弦波的单个周期的一小部分内获得频率的合理估计。我们推导了由加性噪声引起的偏置表达式,并通过实验检验了信号失真的影响
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Constrained least squares estimation of sinusoidal frequencies and application to fast estimation of very low frequency tones
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.<>
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