Underdetermined direction-of-arrival (DOA) estimation for quasi-stationary signals impinging on a uniform circular array (UCA) with M sensors is addressed in this paper. We apply the Khatri–Rao (KR) approach to the UCA and obtain a new signal model which is capable of providing OðMÞ sensors. Meanwhile, the virtual steering matrix can be decomposed into a product of characteristic matrix dependi...

This paper presents the DOA based adaptivebeamforming algorithm of smart antenna systems for mobile communications.Two stages are involved to control the radiation pattern, while maximizing the signal power towards the desired direction and suppressing the interference from undesired direction. The first stage consists of estimating the directions of arrival of all wave fronts impinging on an a...

We propose a new method that detects conversation groups when multi-conversation groups exist simultaneously. The proposed method uses hands-free microphone arrays without wearable microphones. It has two main features: (a) We integrate a conventional turn taking-based conversation detection method with Direction of Arrival (DOA) estimation-based Voice Activity Detection (VAD). (b) The proposed...

Reduced rank linear predictive frequency and direction-of-arrival (DOA) estimation algorithms use the singular value decomposition (SVD) to produce a noise-cleaned linear prediction vector. These algorithms then root this vector to obtain a subset of roots, whose angles contain the desired frequency or DOA information. The roots closest to the unit circle are deemed to be the "signal roots." Th...

Machine learning research has largely been devoted to binary and multiclass problems relating to data mining, text categorization, and pattern/facial recognition. Recently, popular machine learning algorithms have successfully been applied to wireless communication problems, notably spread spectrum receiver design, channel equalization, and adaptive beamforming with direction of arrival estimat...

In this paper, a co-prime symmetric sparse cross array is employed to estimate twodimensional (2-D) direction-of-arrival (DOA). Some special forth-order-cumulants (FOCs) of array received data are used to construct a high-order matrix that is equivalent to a cross-covariance matrix based on two uniform linear arrays. After some modifications, an existing 2-D DOA estimation algorithm becomes mor...

Many signal subspace-based approaches have already been proposed for determining the fixed Direction of Arrival (DOA) of plane waves impinging on an array of sensors. Two procedures for DOA estimation based neural network are presented. Firstly, Principal Component Analysis (PCA) is employed to extract the maximum eigenvalue and eigenvector from signal subspace to estimate DOA. Secondly, Minor ...

In this paper, we firstly construct a wide-band undersampling array, then present a novel frequency and direction of arrival (DOA) estimation method for a very wide frequency band (2-18GHz). Choosing a set of appropriate sampling frequencies and antenna spacing, the method can provide unambiguous frequency and DOA estimation under the sub-Nyquist spatio-temporal sampling. The proposed method ca...

This paper addresses the problem of direction-of-arrival (DOA) estimation of multiple wideband coherent chirp signals, and a new method is proposed. The new method is based on signal component analysis of the array output covariance, instead of the complicated time-frequency analysis used in previous literatures, and thus is more compact and effectively avoids possible signal energy loss during...

This paper deals with the problem of the Direction Of Arrival (DOA) estimation with nonuniform linear arrays. The proposed method is a combination of the Expectation Maximization (EM) and the ESPRIT methods. The EM algorithm interpolates the nonuniform array to an equivalent uniform array, and then, the application of ESPRIT is possible, in order to estimate the DOA. One of this method noveltie...