High-Resolution Direction-of-Arrival Estimation via Concentric Circular Arrays
Author(s) -
Serdar Özgür Ata,
Cevdet Işık
Publication year - 2013
Publication title -
isrn signal processing
Language(s) - English
Resource type - Journals
eISSN - 2090-505X
pISSN - 2090-5041
DOI - 10.1155/2013/859590
Subject(s) - direction of arrival , circular buffer , acoustics , radar , sonar , computer science , sensor array , angle of arrival , signal (programming language) , antenna array , antenna (radio) , concentric , signal to noise ratio (imaging) , noise (video) , algorithm , electronic engineering , mathematics , telecommunications , physics , engineering , geometry , artificial intelligence , machine learning , image (mathematics) , programming language
Estimating the direction of arrival (DOA) of source signals is an important research interest in application areas including radar, sonar, and wireless communications. In this paper, the problem of DOA estimation is addressed on concentric circular antenna arrays (CCA) in detail as an alternative to the well-known geometries of the uniform linear array (ULA) and uniform circular array (UCA). We define the steering matrix of the CCA geometry and investigate the performance analysis of the array in the DOA-estimation problem by simulations that are realized through varying the parameters of signal-to-noise ratio, number of sensors, and resolution angle of sensor arrays by using the MUSIC (Multiple Signal Classification) algorithm. The results present that CCA geometries provide higher angle resolutions compared to UCA geometries and require less physical area for the same number of sensor elements. However, as a cost-increasing effect, higher computational power is needed to estimate the DOA of source signals in CCAs compared to ULAs.
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