Title :
On blind beamforming for multiple non-Gaussian signals and the constant-modulus algorithm
Author :
Sheinvald, Jacob
Author_Institution :
RAFAEL, Haifa, Israel
fDate :
7/1/1998 12:00:00 AM
Abstract :
A new method for blindly separating multiple cochannel non-Gaussian signals received by a sensor array is presented. The method is based on a cumulant-based least-squares criterion that, for identically distributed negative-kurtosis signals, is proven to be identical to the “2-2” constant-modulus (CM) cost function commonly used by CM algorithms. A computationally simple algorithm is proposed to minimize the criterion. The algorithm performs well even when the number of samples is small, thus allowing its application in dynamic environments (e.g., moving emitters). For the special case of two signals only, the minimization is obtained analytically. Simulation results are included
Keywords :
array signal processing; higher order statistics; least squares approximations; minimisation; 2-2 constant-modulus cost function; CM algorithms; blind beamforming; blind separation; computationally simple algorithm; constant-modulus algorithm; cumulant-based least-squares criterion; dynamic environments; identically distributed negative-kurtosis signals; minimization; moving emitters; multiple nonGaussian signals; sensor array; two signal case; Array signal processing; Calibration; Computational modeling; Cost function; Frequency; Jacobian matrices; Minimization methods; Sensor arrays; Sensor phenomena and characterization; Signal analysis;
Journal_Title :
Signal Processing, IEEE Transactions on