This correspondence focuses on the asymptotic performance analysis of general direction-of-arrival (DOA) finding algorithms under the stochastic model assumption in which source and noise signals are possibly non-Gaussian and possibly temporally correlated. We prove, in particular, that all the covariance-based DOA estimators are sensitive to the temporal correlation of the sources when the noi...

Hexagonal arrays are widely used in practice but have received less attention in the optimum array processing literature. In this paper, we show how unitary ESPRIT can be applied to hexagonal arrays for direction-of-arrival (DOA) estimation. The resulting estimates exhibit good threshold behavior, and are close to the Cramer-Rao bound above threshold. We also show how to use spatial smoothing i...

Beamforming remains one of the most common methods for estimating the Direction Of Arrival (DOA) of an acoustic source. Beamformers operate using at least two sensors that look among a set of geometrical directions for the one that maximizes received signal power. In this paper we consider a two-sensor beamformer that estimates the DOA of a single source by scanning the broadside for the direct...

We have seen that there is a one-to-one relationship between the direction of a signal and the associated received steering vector. It should therefore be possible to invert the relationship and estimate the direction of a signal from the received signals. An antenna array therefore should be able to provide for direction of arrival estimation. We have also seen that there is a Fourier relation...

OF THE DISSERTATION Underwater Direction-of-Arrival Finding: Maximum Likelihood Estimation and Performance Analysis by Tao Li Doctor of Philosophy in Electrical Engineering Washington University in St. Louis, May 2012 Research Advisor: Dr. Arye Nehorai In this dissertation, we consider the problems of direction-of-arrival (DOA) finding using acoustic sensor arrays in underwater scenarios, and d...

We present a DOA estimation algorithm, called Joint-Sparse DOA to address the problem of direction-of-arrival (DOA) estimation using sensor arrays. Firstly, DOA estimation is cast as the joint-sparse recovery problem. Then, norm is approximated by an arctan function to represent joint sparsity and DOA estimation can be obtained by minimizing the approximate norm. Finally, the minimization probl...

The estimation of direction of arrival (DOA) is the main study of the direction finding and location of radio signal, MUSIC algorithm is the most classic DOA estimation. MUSIC algorithm can estimate independent signals’ DOA effectively, but it is failure to coherent signals. Concerning the issue, the modified MUSIC algorithm works when the correlative signals exist. However, the estimation perf...

A method to resolve cyclic ambiguities and increase the accuracy and the resolution in the direction-of-arrival (DOA) estimation using the Estimation of Signal Parameters via Rotational Invariance Technique (ESPRIT)algorithm is proposed. It is based on rotating the array and sampling the received signal at multiple positions. Using this approach, the gain in accuracy and resolution is addressed...

In this paper, direction-of-arrival (DOA) estimation of a single narrow-band source with uniform linear arrays is addressed. The basic idea is to convert the received data to a correlation sequence which can be modelled as a noisy sinusoid. Then the computationally attractive and accurate generalized weighted linear predictor frequency estimator is applied for DOA determination. The effectivene...

In this paper, an array aperture extension algorithm is developed for two-dimensional (2-D) direction-of-arrival (DOA) estimation with L-shaped array. We enlarge the dimension of the covariance matrix by using the rotational invariance in conjunction with the property that the signal covariance matrix is real diagonal matrix. Estimation of DOAs is performed by processing this larger dimensional...