Temat: DOA - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Focusing Operators and Tracking Moving Wideband Sources
Autorzy:: Frikel, M.
Safi, S.
Khmou, Y.
Powiązania:: https://bibliotekanauki.pl/articles/309477.pdf
Data publikacji:: 2016
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: DoA
localization
tracking
wideband signal
Opis:: In this paper, the localization of wideband source with an algorithm to track a moving source is investigated. To locate the wideband source, the estimation of two directions of arrival (DOA) of this source from two different arrays of sensors is used, and then, a recursive algorithm is applied to predict the moving source’s position. The DOA is estimated by coherent subspace methods, which use the focusing operators. Practical methods of the estimation of the coherent signal subspace are given and compared. Once the initial position is estimated, an algorithm of tracking the moving source is presented to predict its trajectory.
Źródło:: Journal of Telecommunications and Information Technology; 2016, 4; 53-59
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Performance Comparison of Several Algorithms for Localization of Wideband Sources
Autorzy:: Ougraz, Hassan
Safi, Said
Boumezzough, Ahmed
Frikel, Miloud
Powiązania:: https://bibliotekanauki.pl/articles/24200743.pdf
Data publikacji:: 2023
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: coherent
DOA estimation
incoherent
localization
wideband sources
Opis:: In recent years, researchers have tried to estimate the direction-of-arrival (DOA) of wideband sources and several novel techniques have been proposed. In this paper, we compare six algorithms for calculating the DOA of broadband signals, namely coherent subspace signal method (CSSM), two-sided correlation transformation (TCT), incoherent multiple signal classification (IMUSIC), test of orthogonality of frequency subspaces (TOFS), test of orthogonality of projected subspaces (TOPS), and squared TOPS (S-TOPS). The comparison is made through computer simulations for different parameters, such as signal-to-noise ratio (SNR), in order to establish the efficiency and performance of the discussed methods in noisy environments. CSSM and TCT require initial values, but the remaining approaches do not need any preprocessing.
Źródło:: Journal of Telecommunications and Information Technology; 2023, 3; 21--29
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

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

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Skocz do pozycji: 4.

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

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