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Wyszukujesz frazę "direction-of-arrival estimation" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Localisation of partial discharges sources using acoustic transducers arrays
Autorzy:
Polak, F.
Sikorski, W.
Siodła, K.
Powiązania:
https://bibliotekanauki.pl/articles/97543.pdf
Data publikacji:
2014
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
partial discharge
Signal Source Localisation
Transducer Array
Direction of Arrival (DOA) Estimation
music
Opis:
This paper concerns the issue of the partial discharge (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.
Źródło:
Computer Applications in Electrical Engineering; 2014, 12; 237-245
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Microphone Based Acoustic Vector Sensor for Direction Finding with Bias Removal
Autorzy:
Wajid, Mohd
Kumar, Arun
Bahl, Rajendar
Powiązania:
https://bibliotekanauki.pl/articles/2141636.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
acoustic measurements
acoustic sensor
acoustic vector sensor
direction-of-arrival estimation
finite element analysis
microphones
particle velocity
sound source localization
Opis:
The acoustic vector sensor (AVS) is used to measure the acoustic intensity, which gives the direction-of-arrival (DOA) of an acoustic source. However, while estimating the DOA from the measured acoustic intensity the finite microphone separation (d) in a practical AVS causes angular bias. Also, in the presence of noise there exists a trade off between the bias (strictly increasing function of d) and variance (strictly decreasing function of d) of the DOA estimate. In this paper, we propose a novel method for mitigating the angular bias caused due to finite microphone separation in an AVS. We have reduced the variance by increasing the microphone separation and then removed the bias with the proposed bias model. Our approach employs the finite element method (FEM) and curves fitting to model the angular bias in terms of microphone separations and frequency of a narrowband signal. Further, the bias correction algorithm based on the intensity spectrum has been proposed to improve the DOA estimation accuracy of a broadband signal. Simulation results demonstrate that the proposed bias correction scheme significantly reduces the angular bias and improves the root mean square angular error (RMSAE) in the presence of noise. Experiments have been performed in an acoustic full anechoic room to corroborate the effect of microphone separation on DOA estimation and the efficacy of the bias correction method.
Źródło:
Archives of Acoustics; 2022, 47, 2; 151-167
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
Autorzy:
Mohammed, Jafar Ramadhan
Powiązania:
https://bibliotekanauki.pl/articles/1839475.pdf
Data publikacji:
2021
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
compressed sensing
direction of arrival
DOA
estimation
sparse array
Opis:
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.
Źródło:
Journal of Telecommunications and Information Technology; 2021, 1; 8-14
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
High-resolution Direction of Arrival Estimation Method Based on Sparse Arrays with Minimum Number of Elements
Autorzy:
Mohammed, Jafar Ramadhan
Powiązania:
https://bibliotekanauki.pl/articles/1839489.pdf
Data publikacji:
2021
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
compressed sensing
direction of arrival
DOA
estimation
sparse array
Opis:
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.
Źródło:
Journal of Telecommunications and Information Technology; 2021, 1; 8-14
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

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