Performance analysis of Independent Component Analysis to separate mixtures of complex sinusoidal signals

ICA (independent component analysis) has a remarkable capability of separating mixtures of stochastic random signals. However, we often face problems of separating mixtures of deterministic signals, especially sinusoidal signals, in some applications such as radar systems and communication systems. One may ask if ICA is effective for deterministic signals. In this paper, we analyze basic performance of separating mixtures of complex sinusoidal signals for ICA which utilizes the forth cumulant as a criterion of independency of signals. We theoretically show the ICA can separate mixtures of deterministic sinusoidal signals. Then, we conduct computer simulations and radio experiments with a linear array antenna to confirm the theoretical result. We will show that the ICA is successful to separate mixtures of sinusoidal signals with frequencies close to less than FFT resolution and at DOAs (direction of arrival) close to less than Rayleigh criterion.