IEICE TRANSACTIONS on Communications
Optimization and Hole Interpolation of 2-D Sparse Arrays for Accurate Direction-of-Arrival Estimation
Summary :
This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E104-B No.4 pp.401-409
- Publication Date
- 2021/04/01
- Publicized
- 2020/10/21
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2020EBP3035
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Shogo NAKAMURA
Yokohama National University
Sho IWAZAKI
Yokohama National University
Koichi ICHIGE
Yokohama National University
Keyword
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Shogo NAKAMURA, Sho IWAZAKI, Koichi ICHIGE, "Optimization and Hole Interpolation of 2-D Sparse Arrays for Accurate Direction-of-Arrival Estimation" in IEICE TRANSACTIONS on Communications,
vol. E104-B, no. 4, pp. 401-409, April 2021, doi: 10.1587/transcom.2020EBP3035.
Abstract: This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2020EBP3035/_p
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@ARTICLE{e104-b_4_401,
author={Shogo NAKAMURA, Sho IWAZAKI, Koichi ICHIGE, },
journal={IEICE TRANSACTIONS on Communications},
title={Optimization and Hole Interpolation of 2-D Sparse Arrays for Accurate Direction-of-Arrival Estimation},
year={2021},
volume={E104-B},
number={4},
pages={401-409},
abstract={This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.},
keywords={},
doi={10.1587/transcom.2020EBP3035},
ISSN={1745-1345},
month={April},}
Copy
TY - JOUR
TI - Optimization and Hole Interpolation of 2-D Sparse Arrays for Accurate Direction-of-Arrival Estimation
T2 - IEICE TRANSACTIONS on Communications
SP - 401
EP - 409
AU - Shogo NAKAMURA
AU - Sho IWAZAKI
AU - Koichi ICHIGE
PY - 2021
DO - 10.1587/transcom.2020EBP3035
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E104-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2021
AB - This paper presents a method to optimize 2-D sparse array configurations along with a technique to interpolate holes to accurately estimate the direction of arrival (DOA). Conventional 2-D sparse arrays are often defined using a closed-form representation and have the property that they can create hole-free difference co-arrays that can estimate DOAs of incident signals that outnumber the physical elements. However, this property restricts the array configuration to a limited structure and results in a significant mutual coupling effect between consecutive sensors. In this paper, we introduce an optimization-based method for designing 2-D sparse arrays that enhances flexibility of array configuration as well as DOA estimation accuracy. We also propose a method to interpolate holes in 2-D co-arrays by nuclear norm minimization (NNM) that permits holes and to extend array aperture to further enhance DOA estimation accuracy. The performance of the proposed optimum arrays is evaluated through numerical examples.
ER -
English
