In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.
Thomas BASIKOLO
Yokohama National University
Koichi ICHIGE
Yokohama National University
Hiroyuki ARAI
Yokohama National University
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Thomas BASIKOLO, Koichi ICHIGE, Hiroyuki ARAI, "Nested Circular Array and Its Concentric Extension for Underdetermined Direction of Arrival Estimation" in IEICE TRANSACTIONS on Communications,
vol. E101-B, no. 4, pp. 1076-1084, April 2018, doi: 10.1587/transcom.2017EBP3232.
Abstract: In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3232/_p
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@ARTICLE{e101-b_4_1076,
author={Thomas BASIKOLO, Koichi ICHIGE, Hiroyuki ARAI, },
journal={IEICE TRANSACTIONS on Communications},
title={Nested Circular Array and Its Concentric Extension for Underdetermined Direction of Arrival Estimation},
year={2018},
volume={E101-B},
number={4},
pages={1076-1084},
abstract={In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.},
keywords={},
doi={10.1587/transcom.2017EBP3232},
ISSN={1745-1345},
month={April},}
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TY - JOUR
TI - Nested Circular Array and Its Concentric Extension for Underdetermined Direction of Arrival Estimation
T2 - IEICE TRANSACTIONS on Communications
SP - 1076
EP - 1084
AU - Thomas BASIKOLO
AU - Koichi ICHIGE
AU - Hiroyuki ARAI
PY - 2018
DO - 10.1587/transcom.2017EBP3232
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E101-B
IS - 4
JA - IEICE TRANSACTIONS on Communications
Y1 - April 2018
AB - In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.
ER -