IEICE TRANSACTIONS on Fundamentals
Two Types of Adaptive Beamformer Using 2-D Joint Process Lattice Estimator
Summary :
This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.1 pp.117-122
- Publication Date
- 1998/01/25
- Publicized
- Online ISSN
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- Type of Manuscript
- Category
- Digital Signal Processing
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Tateo YAMAOKA, Takayuki NAKACHI, Nozomu HAMADA, "Two Types of Adaptive Beamformer Using 2-D Joint Process Lattice Estimator" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 1, pp. 117-122, January 1998, doi: .
Abstract: This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_1_117/_p
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@ARTICLE{e81-a_1_117,
author={Tateo YAMAOKA, Takayuki NAKACHI, Nozomu HAMADA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Two Types of Adaptive Beamformer Using 2-D Joint Process Lattice Estimator},
year={1998},
volume={E81-A},
number={1},
pages={117-122},
abstract={This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.},
keywords={},
doi={},
ISSN={},
month={January},}
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TY - JOUR
TI - Two Types of Adaptive Beamformer Using 2-D Joint Process Lattice Estimator
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 117
EP - 122
AU - Tateo YAMAOKA
AU - Takayuki NAKACHI
AU - Nozomu HAMADA
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 1998
AB - This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.
ER -
English
