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Adaptive cancellation of multiple interfering sinusoids

The adaptive sinusoidal interference canceller (ASIC), which gives an estimation of the unknown phase and amplitude, is a least-mean-square (LMS) method for eliminating a sine wave of known frequency from an observed signal. In this paper, the ASIC is generalized to cancel multiple interfering sinusoids with frequencies which are not exactly known. Convergence behavior and mean square errors of the estimates are derived and verified by computer simulations. It is also shown that the ASIC can provide significant signal-to-noise ratio (SNR) improvement. When the inteference frequencies are exactly known, it is proved that the ASIC estimation of phases and amplitudes can attain the Cramer-Rao lower bound (CRLB).