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

We use a previously introduced fast orthogonal search (FOS) algorithm to obtain sinusoidal frequency components buried in either white or colored noise. We show that the method outperforms the correlogram, modified covariance autoregressive (MODCOVAR) and multiple signal classification (MUSIC) methods. The proposed approach using the FOS method achieves accurate detection of sinusoids even with signal-to-noise ratios as low as -17 dB, and is superior at detecting sinusoids 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 process observed in physiological signals such as heart rate and blood pressure data.