Time-difference-of-arrival estimation algorithms for cyclostationary signals in impulsive noise

In this paper, new signal-selective methods for the estimation of time-difference-of-arrival in the presence of interfering signals and non-Gaussian symmetric α-stable impulsive noise are introduced. First, the performance degradation of the conventional approaches based on second-order cyclic statistics is presented. Then, two new classes of robust algorithms are developed using the theory of stable distributions and the cyclostationary property, including the pth-order cyclostationarity methods and the fractional lower-order cyclostationarity methods. It is shown that these new methods are tolerant to interference and robust in both Gaussian and non-Gaussian impulsive noise environments. The improved performance is demonstrated through detailed theoretical analysis and simulations.

► The TDOA estimation for cyclostationary signals in impulsive noise environment is considered. ► Two new types of cyclic statistics are developed to exploit cyclostationarity property. ► Two new classes of signal-selective TDOA algorithms for cyclostationary signals are presented. ► The new cyclic statistics are used in the TDOA methods to suppress interference and noise. ► Simulation results show effectiveness and robustness of the approaches in various scenarios.