Accurate identification of periodic oscillations buried in white or colored noise using fast orthogonal search

We use a previously introduced fast orthogonal search algorithm to detect s inusoidal frequency components buried in either white or colored noise, We show that the method outperforms the correlogram, modified covariance autor egressive (MODCOVAR) and multiple-signal classification (MUSIC) methods. Fa st orthogonal search method achieves accurate detection of sinusoids even w ith signal-to-noise ratios as low as -10 dB, and is superior at detecting s inusoids buried in 1/f noise. Since the utilized method accurately detects sinusoids even under colored noise, it can be used to extract a 1/f noise p rocess observed in physiological signals such as heart rate and renal blood pressure and flow data.