A logarithm-kurtosis based complex algorithm for blind signal extraction and blind beamforming
基于峰度自然对数最大化的信号盲分拣算法和盲波束形成

One source blind extraction can be used to blind beamforming for underwater acoustic arrays. Among existing candidate approaches such as the simple constant modulus Algorithm (CMA), Kurtosis Maximization Algorithm (KMA), etc., KMA can separate both negative and positive kurtosis signals. As KMA is used to separate underwater acoustic signals the convergence rate is low. Present paper applies logarithm of kurtosis to form the objective function, and proposes a one source blind extraction algorithm based on logarithm-kurtosis maximization. At the same time, double deflation algorithms are also proposed to separate more signals in turn. In contrast to KMA convergence rate is improved. A nonlinear function is used in learning so that the algorithm can choose the learning step automatically. Computer simulations verify the proposed algorithm.