Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
IEEE Transactions on Signal Processing
Symmetric alpha-stable filter theory
IEEE Transactions on Signal Processing
Performance analysis of the total least squares ESPRIT algorithm
IEEE Transactions on Signal Processing
Acoustic vector-sensor beamforming and Capon direction estimation
IEEE Transactions on Signal Processing
Identifiability in array processing models with vector-sensorapplications
IEEE Transactions on Signal Processing
Analysis of joint angle-frequency estimation using ESPRIT
IEEE Transactions on Signal Processing
Acoustic vector-sensor array processing
IEEE Transactions on Signal Processing
Data block adaptive filtering algorithms for α-stable random processes
Digital Signal Processing
Performance of RBF neural networks for array processing in impulsive noise environment
Digital Signal Processing
Multidimensional Systems and Signal Processing
Adaptive blind equalization for MIMO systems under α-stable noise environment
IEEE Communications Letters
Space-time blind equalization under α-stable noise environment
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array
Digital Signal Processing
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The class of alpha-stable distributions is better for modeling impulsive noise than Gaussian distribution in array signal processing. After briefly introducing the statistical characteristics of stable distribution and the fractional lower order statistics, including the covariation and the fractional order correlation, this paper proposes a new FOC-ESPRIT method of 2-D direction finding based on the fractional order correlation and subspace technique for underwater 2-D source localization using a vector hydrophones array under alpha-stable noise conditions. A vector hydrophone comprises two or three spatially co-located, orthogonally oriented identical velocity hydrophones (each of which measures one Cartesian component of the underwater acoustical particle velocity vector-field) plus an optional pressure hydrophone. Simulation experiments show that the proposed method is robust in a wide range of characteristic exponent values of stable distribution. Its performances are better than those of the conventional second-order statistics based ESPRIT algorithm, furthermore, the fractional order correlation is more suitable than the covariation in practical applications.