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This paper addresses the statistical performance of subspace DoA estimation using a sensor array, in the asymptotic regime where the number of samples and sensors both converge to infinity at the same rate. Improved subspace DoA estimators were derived (termed as G-MUSIC) in previous works, and were shown to be consistent and asymptotically Gaussian distributed in the case where the number of sources...
We address the problem of pilot decontamination for massive MIMO systems for finite dimensional channels, wherein the channel vectors between the users and the base station are composed of a finite number of discrete paths. The pilot decontamination problem is addressed using high-resolution parametric spectral estimation methods, such as root multiple-signal classification (root-MUSIC), for resolving...
In this paper we propose an adaptive multi user (MU) single-cell hybrid precoding strategy that iteratively designs the precoders/combiners exploiting the reciprocity of time division duplex (TDD) millimeter wave systems. The minimum mean square error (MMSE) criterion is considered to design the combiners, which relies on second order statistics of the channel. The covariance of the received signal...
This paper investigates sound source localisation using an ad-hoc microphone array, where the microphones arbitrarily distributed in a room without knowledge of their locations. The proposed method is applicable to scenarios where microphones positions do not comply with conventional microphone arrays such as a Uniform Linear Array (ULA) and large aperture microphone panels. The proposed method utilizes...
This paper introduces a new direction of arrival (DOA) estimation method for Doppler radars with Multiple-input multiple-output (MIMO) systems, which have been used in various applications, for example, detection and classification of indoor human activities. To improve DOA estimation accuracy, the temporal-spatial virtual array based on Doppler shift of a moving target has been proposed; hereafter...
In this paper, we address the problem of direction-of-arrival (DOA) estimation using a novel spatial sampling scheme based on difference set (DS) codes, called DS-spatial sampling. It is shown that the proposed DS-spatial sampling scheme can be modeled by a deterministic dictionary with minimum coherence. We also develop a low complexity compressed sensing (CS) model for DOA estimation. The proposed...
Joint estimation on direction of departure (DOD) and direction of arrival (DOA) is a key problem in bistatic multiple-input multiple-output (MIMO) radar. The conventional singular value decomposition (SVD) or eigenvalue decomposition (EVD) based subspace algorithms have heavy computational burden when the large transmit/receive array size and snapshots are required. In this paper, a low complexity...
This paper presents a computationally efficient Direction-Of-Arrival (DOA) estimation method for Uniform Rectangular Array (URA), which is effective for both correlated and uncorrelated sources. The proposed method is an extension of our previous study for Uniform Linear Array (ULA), basically based on the relation between the elements of array covariance matrix, does not need iteration, angular peak-search...
High-resolution direction of arrival (DOA) estimation has always been an issue in signal processing field. Most of conventional methods such as Multiple Signal Classification (MUSIC), suffer from lack of resolvability in low signal to noise ratio (SNR) or small number of snapshots whereas computation cost of new methods are considerable. The Compressive MUSIC (CS-MUSIC) algorithm deals with joint...
This research explored the effect of different presentation orders on processing time and time estimation, from the perspective of verbal working memory dual-task mode task. 108 participants took part in memorizing order or disorder French word, it showed that the presentation order significantly shortens the processing time and estimation time, thus it proved that the orderly presentation can enhance...
We consider the problem of estimating the singular vectors of low-rank signal matrices buried in noise in the setting where the singular vectors are assumed to be Kronecker products of three unknown vectors. We propose several algorithms for estimating such singular vectors, which explicitly exploit the Kronecker structure of the underlying vectors. We demonstrate improved estimation accuracy and...
This paper focuses on applying a fourth-order cumulant with spatial smoothing to direction of arrival (DOA) estimation of coherent signals based on a uniform circular array (UCA). We use three types of cumulant matrices in the so-called mode space with spatial smoothing to handle this problem. The DOA estimation performance comparisons of these cumulant matrices with spatial smoothing are shown by...
Automatic approximations of brain volumes are very useful in various researches and clinical practises. The conventional hand tracing is time consuming and the level of accuracy depends on the individual. The present work aims at the automatic estimation of brain volume and 3-D visualization using VTK in a pythonic environment after the edge enhancement and unsharp masking by quadratic filters for...
The Direction of Arrival (DoA) estimation of signals impinging on a failed antenna array is approached as an optimization problem and solved by using particle swarm optimization (PSO) technique with single snapshot. The performance and usefulness of this algorithm is analyzed under different failure scenarios and also in different noisy environment. In this paper we have made a study on the tolerance...
Since a nested phased array cannot directly estimate the range of targets due to range ambiguity, this paper proposes a nested array with diverse time-delayers for target range and angle estimation. The essence is to construct a new array structure by systematically nesting two uniform linear arrays through diverse time-delays which yields a range-dependent receiving array beampattern. Using second-order...
A sequential Bayesian approach to density evolution for sparse source reconstruction is proposed and analysed which alternatingly solves a generalized LASSO problem and its dual. Waves are observed by a sensor array. The waves are emitted by a spatially-sparse set of sources. A weighted Laplace-like prior is assumed for the sources such that the maximum a posteriori source estimate at the current...
This paper presents an accurate source number detection method for low-cost array system based on nested array and Khatri-Rao product approaches. Source number estimation accuracy can be enhanced by increasing the number of array elements, but it is often limited due to hardware and software cost. The authors have already proposed a low-cost array receiver system using switches which can reduce receiver...
In this paper, we focus on the effective Space-Time Adaptive Processing (STAP) method in nonhomogeneous clutter environment. The nonhomogeneous clutter leads to the lack of sufficient training data for clutter covariance matrix estimation in traditional STAP methods. By utilizing the sparsity of the distribution of clutter in angle-Doppler domain, we build a factor graph model and develop a message...
Direction-of-arrival (DOA) estimation involves the localization of a few sources from a limited number of observations on an array of sensors. Thus, DOA estimation can be formulated as a sparse signal reconstruction problem and solved efficiently with compressive sensing (CS) to achieve high-resolution imaging. Utilizing the dual optimal variables of the CS optimization problem, it is shown with Monte...
This paper describes the development of a portable electronic percussion musical instrument based on movement sensing and signal processing. The system captures the movements from drumsticks and pedals using three-axis accelerometers to translate them into MIDI (Musical Instrument Digital Interface) messages, applying an eigenfilter identification algorithm implemented on a microcontroller. The messages...
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