relation: https://khub.utp.edu.my/scholars/16221/
title: Performance Investigation of Linearly Arranged Circular, Circular Planer, Rectangular, and Concentric Circular Antenna Arrays Using Robust NVL Techniques
creator: Rahaman, I.
creator: Jafor, M.S.
creator: Singh, N.S.S.
creator: Haque, M.A.
creator: Biswas, A.K.
creator: Rahman, M.A.
creator: Zakariya, M.A.B.
creator: Abro, G.E.M.
creator: Sarker, N.
description: In this research, linearly arranged circular antenna array (LCAA), linearly arranged circular planer antenna array (LCPAA), linearly arranged rectangular antenna array (LRAA), and linearly arranged concentric circular antenna array (LCCAA) are analyzed using robust techniques. These four antenna arrays are briefly investigated to evaluate their beam width performance, ability to detect a false signal, and SINR power pattern performances. Robust techniques�fixed diagonal loading (FDL), optimal diagonal loading (ODL), variable diagonal loading (VDL), and new variable loading (NVL) techniques�are applied, and the NVL technique is found to be superior and provides the best performance with the proposed LCCAA beamformer. With an SINR of 40.45 dB, 40.29 dB, 40.18 dB, and 39.99 dB for 0°, 1°, 2°, and 3° disparity angles, respectively, and output powers of �0.019 dB, �0.076 dB, and �0.171 dB for 1°, 2°, and 3° disparity angles, respectively, LCCAA beamformers using the NVL technique outperform other beamformers with different robust approaches. © 2022 by the authors.
publisher: MDPI
date: 2022
type: Article
type: PeerReviewed
identifier:   Rahaman, I. and Jafor, M.S. and Singh, N.S.S. and Haque, M.A. and Biswas, A.K. and Rahman, M.A. and Zakariya, M.A.B. and Abro, G.E.M. and Sarker, N.  (2022) Performance Investigation of Linearly Arranged Circular, Circular Planer, Rectangular, and Concentric Circular Antenna Arrays Using Robust NVL Techniques.  Applied Sciences (Switzerland), 12 (22).   ISSN 20763417     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142492392&doi=10.3390%2fapp122211481&partnerID=40&md5=49367089e0c6416644baf0a50e645b78
relation: 10.3390/app122211481
identifier: 10.3390/app122211481