Robust spatial filtering of coherent sources for wireless communications
Signal Processing
Cyclostationarity: half a century of research
Signal Processing
TDOA estimation for cyclostationary sources: New correlations-based bounds and estimators
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Underwater sources location in non-Gaussian impulsive noise environments
Digital Signal Processing
Statistical modeling of co-channel interference
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
A comparison of stationary and cyclostationary TDOA estimators
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Robust multiuser detection in non-Gaussian channels
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A Parametric Approach to Suboptimal Signal Detection in -Stable Noise
IEEE Transactions on Signal Processing
The stability test for symmetric alpha-stable distributions
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Estimation of Second-Order Cross-Moments of Generalized Almost-Cyclostationary Processes
IEEE Transactions on Information Theory
Asymptotic theory of mixed time averages and kth-order cyclic-moment and cumulant statistics
IEEE Transactions on Information Theory
An ℓp-norm minimization approach to time delay estimation in impulsive noise
Digital Signal Processing
Hi-index | 0.08 |
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 @a-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.