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EN
Regular fully filled antenna arrays have been widely used in direction of arrival (DOA) estimation. However, practical implementation of these arrays is rather complex and their resolutions are limited to the beamwidth of the array pattern. Therefore, higher resolution and simpler methods are desirable. In this paper, the compressed sensing method is first applied to an initial fully filled array to randomly select the most prominent and effective elements which are used to form the sparse array. To keep the dimension of the sparse array equal to that of the fully filled array, the first and the last elements were excluded from the sparseness process. In addition, some constraints on the sparse spectrum are applied to increase estimation accuracy. The optimization problem is then solved iteratively using the iterative reweighted l1 norm. Finally, a simple searching algorithm is used to detect peaks in the spectrum solution that correspond to the directions of the arriving signals. Compared with the existing scanned beam methods, such as the minimum variance distortionless response (MVDR) technique, and with subspace approaches, such as multiple signal classification (MUSIC) and ESPIRT algorithms, the proposed sparse array method offers better performance even with a lower number of array elements and in severely noisy environments. Effectiveness of the proposed sparse array method is verified via computer simulations.
EN
A single acoustic vector sensor (AVS) cannot be used to find the direction-of-arrival (DOA) of two or more coherent (fully correlated) sources. We have proposed a technique for estimating DOAs (in 2D geometry) of two simultaneous coherent sources using single AVS under the assumption that acoustic sources enter in the field sequentially. The DOA estimation has been investigated with two different configurations of AVS, each consisting of three microphones in a plane. The technique has been also applied in tracking (a) an acoustic source in the presence of stationary interfering coherent source and (b) two coherent sources when the sources are changing their locations alternatively. The experimental environment has been generated using the Finite-Element Method tool viz. COMSOL to corroborate the proposed scheme.
3
EN
This paper presents the main technical characteristics and working performances of coastal maritime surveillance radars, such as low-power High-Frequency Surface Wave Radars (HFSWR) and Over the Horizon Radars (OTHR). These radars have demonstrated to be a cost-effective long-range early-warning sensor for ship detection and tracking in coastal waters, sea channels and passages. In this work, multi-target tracking and data fusion techniques are applied to live-recorded data from a network of oceanographic HFSWR stations installed in Jindalee Operational Radar Network (JORN), Wellen Radar (WERA) in Ligurian Sea (Mediterranean Sea), CODAR Ocean Sebsorsin and in the German Bight (North Sea). The coastal Imaging Sciences Research (ISR) HFSWR system, Multi-static ISR HF Radar, Ship Classification using Multi-Frequency HF Radar, Coastal HF radar surveillance of pirate boats and Different projects of coastal HF radars for vessels detecting are described. Ship reports from the Automatic Identification System (AIS), recorded from both coastal and satellite Land Earth Stations (LES) are exploited as ground truth information and a methodology is applied to classify the fused tracks and to estimate system performances. Experimental results for all above solutions are presented and discussed, together with an outline for future integration and infrastructures.
EN
Assuming independently but identically distributed sources, the traditional DOA (direction of arrival) estimation method of underwater acoustic target normally has poor estimation performance and provides inaccurate estimation results. To solve this problem, a new high-accuracy DOA algorithm based on sparse Bayesian learning algorithm is proposed in terms of temporally correlated source vectors. In novel method, we regarded underwater acoustic source as a first-order auto-regressive process. And then we used the new algorithm of multi-vector SBL to reconstruct the signal spatial spectrum. Then we used the CS-MMV model to estimate the DOA. The experiment results have shown the novel algorithm has a higher spatial resolution and estimation accuracy than other DOA algorithms in the cases of less array element space and less snapshots.
EN
The paper demonstrates the use of frequency reassignment for bearing estimation. For this task, signals derived from a linear equispaced passive array are used. The presented method makes use of Fourier transformation based spatial spectrum estimation. It is further developed through the application of two-dimensional reassignment, which leads to obtaining highly concentrated energy distributions in the joint frequency-angle domain and sharp graphical imaging. The introduced method can be used for analysing, a priori, unknown signals of broadband, nonstationary, and/or multicomponent type. For such signals, the direction of arrival is obtained based upon the marginal energy distribution in the angle domain, through searching for arguments of its maxima. In the paper, bearing estimation of three popular types of sonar pulses, including linear and hyperbolic frequency modulated pulses, as well as no frequency modulation at all, is considered. The results of numerical experiments performed in the presence of additive white Gaussian noise are presented and compared to conventional digital sum-delay beamforming performed in the time domain. The root-mean-square error and the peak-to-average power ratio, also known as the crest factor, are introduced in order to estimate, respectively, the accuracy of the methods and the sharpness of the obtained energy distributions in the angle domain.
EN
This article presents a new approach to determine the model order (number of principal components) in the modified Prony method applied to swath acoustic mapping. Determination of the number of principal components is a crucial step in the modified Prony method. In the proposed approach the model order is chosen based on the underlying physical model of the underwater acoustic environment, and utilised signal processing operations. This data-driven approach, attempts to make use of all available information to assess the number of signals arriving at the receiver using pipeline processing in lieu of iterative processing.
EN
This article presents the performance of a new approach to determine the model order for the modified Prony method applied to swath acoustic mapping. Key requirements for any mapping application are depth determination accuracy and angular resolution. Depth determination accuracy is strictly related to angular accuracy and geometrical relations between receiver and sources of the backscattered signal. Angular resolution determines detection capabilities of targets laying on the seafloor. Performance of the proposed method, in terms of these two parameters, is tested against a simulated signal in a number of generic configurations, and compared to the results of other methods applied to the same signal.
PL
W pracy zaprezentowany został prototypowy układ pomiarowy służący do lokalizacji źródeł sygnałów dźwiękowych, pochodzących od wyładowań niezupełnych, opierający się na technologii matryc sensorowych oraz algorytmów estymacji kierunku nadejścia sygnałów. Sygnały akustyczne odbierane są przy pomocy liniowej matrycy sensorów, w której elementami sensorycznymi są mikrofony pracujące w zakresie częstotliwości słyszalnych. Do estymacji kierunku nadejścia tych sygnałów użyto klasycznego algorytmu kształtowania wiązki, którego założenia teoretyczne zawarto w pracy. Docelowo układ będzie służył do określania lokalizacji źródła sygnałów akustycznych generowanych przez wyładowanie ulotowe.
EN
This paper presents a prototype measurement system, that will be used for localisation of acoustic emission sources. It is based on sensor arrays technology and direction of arrival estimation algorithms. Acoustic signals will be received with a universal linear array (ULA) of sensors, wherein the sensory elements are microphones operating in the audible frequency range. For the estimation of the direction of arrival of these signals conventional beamforming algorithm is used which has also been described theoretically. Ultimately, the system will be used to determine the direction of arrival of the acoustic signal generated by the insulation defect, which is corona discharge.
9
Content available remote Lokalizacja źródeł wyładowań niezupełnych przy użyciu matryc sensorowych
PL
W artykule poruszono problematykę lokalizacji źródeł wyładowań niezupełnych przy użyciu matryc sensorowych oraz wysokorozdzielczej techniki estymacji kierunku nadejścia sygnału. W pracy przedstawiono wyniki symulacji, w których sygnały, generowane przez defekty układu izolacyjnego transformatora energetycznego, rejestrowane były za pomocą kwadratowej matrycy sensorowej, natomiast do estymacji kierunku nadejścia tych sygnałów użyto algorytmu MVDR.
EN
This article raises the issue of partial discharge sources location using sensor arrays and the high-resolution direction of arrival estimation technique. The paper presents the results of the simulations, in which the signals generated by defects in power transformer insulation system are collected using a rectangular sensor array, while the direction of arrival estimation of those signals is done by the MVDR algorithm.
PL
Artykuł dotyczy problematyki lokalizacji źródeł wyładowań niezupełnych (wnz) przy użyciu techniki matryc przetworników emisji akustycznej oraz wysokorozdzielczej techniki estymacji kierunku nadejścia sygnału. W pracy, oprócz założeń teoretycznych obu technik, przedstawiono wyniki symulacji, w których do rejestracji sygnałów emisji akustycznej generowanych przez defekty układu izolacyjnego transformatora energetycznego, zastosowano liniową matrycę przetworników (ang. ULA - Uniform Linear Array). Z kolei do estymacji kierunku nadejścia sygnałów akustycznych, które propagują się od defektu generującego wyładowania do zainstalowanej na kadzi transformatora matrycy przetworników, wybrano algorytm Multiple Signal Classification (MUSIC). Dzięki możliwości lokalizacji wyładowań wieloźródłowych (nawet przy bardzo niskim stosunku sygnału użytecznego od szumu), przyjęte rozwiązanie wykazuje przewagę nad technikami konwencjonalnymi.
EN
This paper concerns the issue of partial discharges (PD) sources location using acoustic emission transducer arrays technique and the high resolution direction of arrival estimation technology. In addition to the theoretical assumptions of both techniques, the simulation result, in which an uniform linear array (ULA) was used for registration of the acoustic emission signals generated by defects in power transformer insulation system, were shown. To estimate the direction of arrival (DOA) of acoustic signals, that propagate from the discharge-generating defect to the transducer array installed on transformer tank, Multiple Signal Classification (MUSIC) algorithm was chosen. With the ability to locate multisource discharges (even at very low signal to noise ratio - SNR), the adopted solution has advantages over conventional techniques.
EN
The determination of the number of the simultaneously observed objects is an important problem of the MUSIC algorithm. As the result of the covariance matrix eigendecomposition the eingevector and unitary matrix are obtained. The unitary matrix defines the transformation of the measurement vector. Consequently the obtained vector is orthogonal to the noise subspace. The solution of the eigendecomposition problem can be avoided assuming a-priori knowledge of the unitary matrix. Practically, the passive sonar detects the first appeared noisy object. This enable to beforehand define the set of the unitary matrixes exactly matched to the previously determined directions of the signal arrival. The article presents the form of the matrix and features of the measurement vector transformation. The results of the DOA algorithm computer simulation for passive sonar composed of four hydrophones developed in the OBR CTM S.A. are also presented.
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