Adaptive Beamforming with Sidelobe Suppression by Placing Extra Radiation Pattern Nulls

Ioannis P. Gravas, Zaharias D. Zaharis, Traianos V. Yioultsis, Pavlos Lazaridis, Thomas D. Xenos

Research output: Contribution to journalArticle

Abstract

A new iterative adaptive beamforming (ABF) algorithm based on conventional beamformers is proposed in order not only to steer the main lobe toward the desired signal and place radiation pattern nulls toward respective interference signals but also to achieve the desired sidelobe level (SLL). Thus, the algorithm becomes less susceptible to unpredicted interference signals than conventional beamformers. In each iteration, the algorithm finds the direction of the peak of the greatest sidelobe, which is considered as direction of arrival (DoA) of a hypothetical interference signal, and the conventional beamformer is then employed to find proper antenna array weights that produce an extra null toward this direction. The iterative procedure stops when the desired SLL is obtained. The algorithm is applied on three conventional beamformers and is tested for various signal DoA, while the direction deviation of the main lobe and the nulls is recorded, to evaluate the algorithm in terms of robustness. The proposed algorithm needs a few iterations to achieve the desired SLL and thus is much faster than any evolutionary iterative method employed for sidelobe suppression. Finally, unlike methods that employ neural networks (NNs), the proposed algorithm does not need any training to become functional.

LanguageEnglish
Article number8668532
Pages3853-3862
Number of pages10
JournalIEEE Transactions on Antennas and Propagation
Volume67
Issue number6
Early online date18 Mar 2019
DOIs
Publication statusPublished - 1 Jun 2019

Fingerprint

Beamforming
Signal interference
Direction of arrival
Iterative methods
Antenna arrays
Neural networks

Cite this

Gravas, Ioannis P. ; Zaharis, Zaharias D. ; Yioultsis, Traianos V. ; Lazaridis, Pavlos ; Xenos, Thomas D. / Adaptive Beamforming with Sidelobe Suppression by Placing Extra Radiation Pattern Nulls. In: IEEE Transactions on Antennas and Propagation. 2019 ; Vol. 67, No. 6. pp. 3853-3862.
@article{6c17f2edcdc64293845361e8a8041b85,
title = "Adaptive Beamforming with Sidelobe Suppression by Placing Extra Radiation Pattern Nulls",
abstract = "A new iterative adaptive beamforming (ABF) algorithm based on conventional beamformers is proposed in order not only to steer the main lobe toward the desired signal and place radiation pattern nulls toward respective interference signals but also to achieve the desired sidelobe level (SLL). Thus, the algorithm becomes less susceptible to unpredicted interference signals than conventional beamformers. In each iteration, the algorithm finds the direction of the peak of the greatest sidelobe, which is considered as direction of arrival (DoA) of a hypothetical interference signal, and the conventional beamformer is then employed to find proper antenna array weights that produce an extra null toward this direction. The iterative procedure stops when the desired SLL is obtained. The algorithm is applied on three conventional beamformers and is tested for various signal DoA, while the direction deviation of the main lobe and the nulls is recorded, to evaluate the algorithm in terms of robustness. The proposed algorithm needs a few iterations to achieve the desired SLL and thus is much faster than any evolutionary iterative method employed for sidelobe suppression. Finally, unlike methods that employ neural networks (NNs), the proposed algorithm does not need any training to become functional.",
keywords = "Side lobe level, Beamforming, Minimum variance, Adaptive algorithm, Adaptive beamforming, Distortionless response, Recursive least squares, Sample matrix inversion, Side lobe suppression, sidelobe level (SLL), minimum variance distortionless response (MVDR), Adaptive beamforming (ABF), sidelobe suppression, recursive least squares (RLS), sample matrix inversion (SMI)",
author = "Gravas, {Ioannis P.} and Zaharis, {Zaharias D.} and Yioultsis, {Traianos V.} and Pavlos Lazaridis and Xenos, {Thomas D.}",
year = "2019",
month = "6",
day = "1",
doi = "10.1109/TAP.2019.2905709",
language = "English",
volume = "67",
pages = "3853--3862",
journal = "IEEE Transactions on Antennas and Propagation",
issn = "0018-926X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "6",

}

Adaptive Beamforming with Sidelobe Suppression by Placing Extra Radiation Pattern Nulls. / Gravas, Ioannis P.; Zaharis, Zaharias D.; Yioultsis, Traianos V.; Lazaridis, Pavlos; Xenos, Thomas D.

In: IEEE Transactions on Antennas and Propagation, Vol. 67, No. 6, 8668532, 01.06.2019, p. 3853-3862.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Adaptive Beamforming with Sidelobe Suppression by Placing Extra Radiation Pattern Nulls

AU - Gravas, Ioannis P.

AU - Zaharis, Zaharias D.

AU - Yioultsis, Traianos V.

AU - Lazaridis, Pavlos

AU - Xenos, Thomas D.

PY - 2019/6/1

Y1 - 2019/6/1

N2 - A new iterative adaptive beamforming (ABF) algorithm based on conventional beamformers is proposed in order not only to steer the main lobe toward the desired signal and place radiation pattern nulls toward respective interference signals but also to achieve the desired sidelobe level (SLL). Thus, the algorithm becomes less susceptible to unpredicted interference signals than conventional beamformers. In each iteration, the algorithm finds the direction of the peak of the greatest sidelobe, which is considered as direction of arrival (DoA) of a hypothetical interference signal, and the conventional beamformer is then employed to find proper antenna array weights that produce an extra null toward this direction. The iterative procedure stops when the desired SLL is obtained. The algorithm is applied on three conventional beamformers and is tested for various signal DoA, while the direction deviation of the main lobe and the nulls is recorded, to evaluate the algorithm in terms of robustness. The proposed algorithm needs a few iterations to achieve the desired SLL and thus is much faster than any evolutionary iterative method employed for sidelobe suppression. Finally, unlike methods that employ neural networks (NNs), the proposed algorithm does not need any training to become functional.

AB - A new iterative adaptive beamforming (ABF) algorithm based on conventional beamformers is proposed in order not only to steer the main lobe toward the desired signal and place radiation pattern nulls toward respective interference signals but also to achieve the desired sidelobe level (SLL). Thus, the algorithm becomes less susceptible to unpredicted interference signals than conventional beamformers. In each iteration, the algorithm finds the direction of the peak of the greatest sidelobe, which is considered as direction of arrival (DoA) of a hypothetical interference signal, and the conventional beamformer is then employed to find proper antenna array weights that produce an extra null toward this direction. The iterative procedure stops when the desired SLL is obtained. The algorithm is applied on three conventional beamformers and is tested for various signal DoA, while the direction deviation of the main lobe and the nulls is recorded, to evaluate the algorithm in terms of robustness. The proposed algorithm needs a few iterations to achieve the desired SLL and thus is much faster than any evolutionary iterative method employed for sidelobe suppression. Finally, unlike methods that employ neural networks (NNs), the proposed algorithm does not need any training to become functional.

KW - Side lobe level

KW - Beamforming

KW - Minimum variance

KW - Adaptive algorithm

KW - Adaptive beamforming

KW - Distortionless response

KW - Recursive least squares

KW - Sample matrix inversion

KW - Side lobe suppression

KW - sidelobe level (SLL)

KW - minimum variance distortionless response (MVDR)

KW - Adaptive beamforming (ABF)

KW - sidelobe suppression

KW - recursive least squares (RLS)

KW - sample matrix inversion (SMI)

UR - http://www.scopus.com/inward/record.url?scp=85066985087&partnerID=8YFLogxK

U2 - 10.1109/TAP.2019.2905709

DO - 10.1109/TAP.2019.2905709

M3 - Article

VL - 67

SP - 3853

EP - 3862

JO - IEEE Transactions on Antennas and Propagation

T2 - IEEE Transactions on Antennas and Propagation

JF - IEEE Transactions on Antennas and Propagation

SN - 0018-926X

IS - 6

M1 - 8668532

ER -