Abstract: Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.
Abstract: This paper treats different aspects of entropy measure
in classical information theory and statistical quantum mechanics, it
presents the possibility of extending the definition of Von Neumann
entropy to image and array processing. In the first part, we generalize
the quantum entropy using singular values of arbitrary rectangular
matrices to measure the randomness and the quality of denoising
operation, this new definition of entropy can be implemented to
compare the performance analysis of filtering methods. In the second
part, we apply the concept of pure state in quantum formalism
to generalize the maximum entropy method for narrowband and
farfield source localization problem. Several computer simulation
results are illustrated to demonstrate the effectiveness of the proposed
techniques.
Abstract: Neural activity in the human brain starts from the
early stages of prenatal development. This activity or signals
generated by the brain are electrical in nature and represent not only
the brain function but also the status of the whole body. At the
present moment, three methods can record functional and
physiological changes within the brain with high temporal resolution
of neuronal interactions at the network level: the
electroencephalogram (EEG), the magnet oencephalogram (MEG),
and functional magnetic resonance imaging (fMRI); each of these has
advantages and shortcomings. EEG recording with a large number of
electrodes is now feasible in clinical practice. Multichannel EEG
recorded from the scalp surface provides very valuable but indirect
information about the source distribution. However, deep electrode
measurements yield more reliable information about the source
locations intracranial recordings and scalp EEG are used with the
source imaging techniques to determine the locations and strengths of
the epileptic activity. As a source localization method, Low
Resolution Electro-Magnetic Tomography (LORETA) is solved for
the realistic geometry based on both forward methods, the Boundary
Element Method (BEM) and the Finite Difference Method (FDM). In
this paper, we review the findings EEG- LORETA about epilepsy.
Abstract: The Maximum entropy principle in spectral analysis
was used as an estimator of Direction of Arrival (DoA) of
electromagnetic or acoustic sources impinging on an array of sensors,
indeed the maximum entropy operator is very efficient when the
signals of the radiating sources are ergodic and complex zero mean
random processes which is the case for cosmic sources. In this paper,
we present basic review of the maximum entropy method (MEM)
which consists of rank one operator but not a projector, and we
elaborate a new operator which is full rank and sum of all possible
projectors. Two dimensional Simulation results based on Monte
Carlo trials prove the resolution power of the new operator where the
MEM presents some erroneous fluctuations.
Abstract: In this study, we consider a special situation that only a pair of hydrophone on a moving underwater vehicle is available to localize a fixed acoustic source of far distance. The trigonometry can be used in this situation by using two different DOA of different locations. Notice that the distance between the two locations should be measured. Therefore, we assume that the vehicle is sailing straightly and the moving distance for each unit time is measured continuously. However, the accuracy of the localization using the trigonometry is highly dependent to the accuracy of DOAs and measured moving distances. Therefore, we proposed another method based on the extended Kalman filter that gives more robust and accurate localization result.
Abstract: Acoustic Imaging based sound localization using microphone
array is a challenging task in digital-signal processing.
Discrete Fourier transform (DFT) based near-field acoustical holography
(NAH) is an important acoustical technique for sound source
localization and provide an efficient solution to the ill-posed problem.
However, in practice, due to the usage of small curtailed aperture
and its consequence of significant spectral leakage, the DFT could
not reconstruct the active-region-of-sound (AROS) effectively, especially
near the edges of aperture. In this paper, we emphasize the
fundamental problems of DFT-based NAH, provide a solution to
spectral leakage effect by the extrapolation based on linear predictive
coding and 2D Tukey windowing. This approach has been tested to
localize the single and multi-point sound sources. We observe that
incorporating extrapolation technique increases the spatial resolution,
localization accuracy and reduces spectral leakage when small curtail
aperture with a lower number of sensors accounts.
Abstract: Visualizing sound and noise often help us to determine
an appropriate control over the source localization. Near-field acoustic
holography (NAH) is a powerful tool for the ill-posed problem.
However, in practice, due to the small finite aperture size, the discrete
Fourier transform, FFT based NAH couldn-t predict the activeregion-
of-interest (AROI) over the edges of the plane. Theoretically
few approaches were proposed for solving finite aperture problem.
However most of these methods are not quite compatible for the
practical implementation, especially near the edge of the source. In
this paper, a zip-stuffing extrapolation approach has suggested with
2D Kaiser window. It is operated on wavenumber complex space
to localize the predicted sources. We numerically form a practice
environment with touch impact databases to test the localization of
sound source. It is observed that zip-stuffing aperture extrapolation
and 2D window with evanescent components provide more accuracy
especially in the small aperture and its derivatives.
Abstract: Power cables are vulnerable to failure due to aging or
defects that occur with the passage of time under continuous
operation and loading stresses. PD detection and characterization
provide information on the location, nature, form and extent of the
degradation. As a result, PD monitoring has become an important
part of condition based maintenance (CBM) program among power
utilities. Online partial discharge (PD) localization of defect sources
in power cable system is possible using the time of flight method.
The information regarding the time difference between the main and
reflected pulses and cable length can help in locating the partial
discharge source along the cable length. However, if the length of
the cable is not known and the defect source is located at the extreme
ends of the cable or in the middle of the cable, then double ended
measurement is required to indicate the location of PD source. Use of
multiple sensors can also help in discriminating the cable PD or local/
external PD. This paper presents the experience and results from
online partial discharge measurements conducted in the laboratory
and the challenges in partial discharge source localization.
Abstract: Array signal processing involves signal enumeration and source localization. Array signal processing is centered on the ability to fuse temporal and spatial information captured via sampling signals emitted from a number of sources at the sensors of an array in order to carry out a specific estimation task: source characteristics (mainly localization of the sources) and/or array characteristics (mainly array geometry) estimation. Array signal processing is a part of signal processing that uses sensors organized in patterns or arrays, to detect signals and to determine information about them. Beamforming is a general signal processing technique used to control the directionality of the reception or transmission of a signal. Using Beamforming we can direct the majority of signal energy we receive from a group of array. Multiple signal classification (MUSIC) is a highly popular eigenstructure-based estimation method of direction of arrival (DOA) with high resolution. This Paper enumerates the effect of missing sensors in DOA estimation. The accuracy of the MUSIC-based DOA estimation is degraded significantly both by the effects of the missing sensors among the receiving array elements and the unequal channel gain and phase errors of the receiver.
Abstract: This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.