Obiekt

Tytuł: DOA Estimation of Linear Dipole Arrays Based on Horse Herd Optimization Algorithm, Journal of Telecommunications and Information Technology, 2026, nr 1

Autor:

Bensalem, Mohamed ; Barkat, Ouarda

Data wydania:

2026, nr 1

Typ zasobu:

artykuł

Tytuł publikacji grupowej:

2026, nr 1, JTIT-artykuły

Opis:

kwartalnik

Abstrakt:

Subspace-based direction of arrival (DOA) estimation algorithms, such as MUSIC and ESPRIT, are designed for adaptive smart antenna arrays. However, these subspace methods require a large number of signal snapshots and sufficient angular separation between signals to provide an accurate DOA estimation of RF signal sources. Moreover, their resolution degrades significantly in severe noise scenarios. This study proposes a swarm intelligence (SI) algorithm, known as horse herd optimization (HOA), to address these limitations. An optimizer is employed as a direction-finding method to estimate the directions of arrival (DoAs) of incident signals impinging on a linear array of half-wavelength dipole (HWD) antennas by examining the global minimum of a non-linear cost function. This cost function is defined as the difference between the actual and estimated angles and is used to evaluate candidate solutions. Simulation results of the proposed algorithm have been compared with other recognized algorithms, including ESPRIT, root-MUSIC, and PSO, to verify estimation accuracy, convergence behavior, robustness against the number of elements, noise, and snapshots over Monte Carlo trials. It has been observed that the suggested HOA achieves better performance with a few snapshots, outperforms PSO and subspace-based methods when it comes to estimating DOA of incoming signals, particularly in a low signal-to-noise ratio (SNR) environment, and even when only fewer snapshots are available.

Numer:

1

Wydawca:

National Institute of Telecommunications

Identyfikator zasobu:

oai:bc.itl.waw.pl:2429

DOI:

10.26636/jtit.2026.1.2422

eISSN:

1899-8852

Źródło:

Journal of Telecommunications and Information Technology

Język:

ang

Prawa:

Biblioteka Naukowa Instytutu Łączności

Licencja:

CC BY 4.0

Kolekcje, do których przypisany jest obiekt:

Data ostatniej modyfikacji:

1 kwi 2026

Data dodania obiektu:

1 kwi 2026

Liczba wyświetleń treści obiektu:

2

Wszystkie dostępne wersje tego obiektu:

https://bc.itl.waw.pl/publication/2750

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