This paper introduces a new hybrid of genetic algorithm (GA) and iteration beamspace multiple signal classification (IBMUSIC) suitable for making direction-of-arrival (DOA) in coherent signals. In general, the problem of estimation the DOA in coherent signals is more difficult to solve and conventional DOA estimation methods such as minimum variance distortionless response (MVDR) and multiple s...

An adaptive beamformer that is robust to uncertainty in source direction-of-arrival (DOA) is derived using a Bayesian approach. The DOA is assumed to be a discrete random variable with a known a priori probability density function (pdf) that reflects the level of uncertainty in the source DOA. The resulting beamformer is a weighted sum of minimum variance distortionless response (MVDR) beamform...

In this paper, ‘T’ character-type array antenna system is proposed which estimates the directions of arrival (DOA) by the virtual uniform rectangular arrays. The proposed system consists of 4 antenna elements distributed like the character ‘T’. The performance of the proposed system in DOA estimation is evaluated by some simulation and experiments. First we show that DOA is estimated correctly ...

This paper addresses the problem of direction-of-arrival (DOA) estimation of correlated and coherent signals, and two sparsityinducing methods are proposed. In the first method named L1-EVD, the signal-subspace eigenvectors are represented jointly with wellchosen hard thresholds attached to the representation residue of each eigenvector. Then only the eigenvector corresponding to the largest ei...

In this paper, DOA estimation is an important research area in array signal processing. The performance of adaptive beamforming methods are known to degrade severly in the presence of uncertainty in the signal sight direction. We propose a novel adaptive beamforming with a Bayesian method. Bayesian method a posterior probability density DOA estimator has been shown to perform excellently. The p...

March 1, 2016 The directions of arrival (DOA) of plane waves are estimated from multi-snapshot sensor array data using Sparse Bayesian Learning (SBL). The prior source amplitudes is assumed independent zero-mean complex Gaussian distributed with hyperparameters the unknown variances (i.e. the source powers). For a complex Gaussian likelihood with hyperparameter the unknown noise variance, the c...

Two signal selective Unitary Cyclic DOA algorithms are presented by introducing a new forward-backward smoothed covariance matrix. Compared with conventional Cyclic DOA algorithms, the suggested approaches have better performance in the presence of multipath propagation. In addition, these approaches not only allow to select desired signals and to ignore interferences by exploiting the cyclosta...