Improved time difference of arrival estimation algorithms for cyclostationary signals in α-stable impulsive noise

In this study, we introduce two new robust signal-selective algorithms based on the fractional lower-order cyclostationarity in order to address the problem of estimating time difference of arrival (TDOA) for cyclostationary signals in the presence of interference and α-stable distribution impulsive noise. Conventional signal-selective and fractional lower-order statistics (FLOS) based TDOA methods suffer performance degradation in the presence of non-Gaussian α-stable impulsive noise and corruptive interfering signals. By exploiting fractional lower-order cyclostationarity, we are able to develop a novel multi-cycle method and a generalized fractional lower-order spectral coherence method. The proposed methods restrain the effects of α-stable impulsive noise and make better use of the cyclostationarity property of cyclostationary signals. Simulation results indicate that the new methods are highly tolerant to interference and impulsive noise, and provide higher estimation accuracy than conventional algorithms.