| Item type |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2017-12-14 |
| タイトル |
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|
タイトル |
Efficient AM Algorithms for Stochastic ML Estimation of DOA |
|
言語 |
en |
| 言語 |
|
|
言語 |
eng |
| 資源タイプ |
|
|
資源 |
http://purl.org/coar/resource_type/c_6501 |
|
タイプ |
journal article |
| アクセス権 |
|
|
アクセス権 |
open access |
|
アクセス権URI |
http://purl.org/coar/access_right/c_abf2 |
| 著者 |
Chen, Haihua
Li, Shibao
Liu, Jianhang
Zhou, Yiqing
Suzuki, Masakiyo
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| 著者別名 |
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識別子Scheme |
WEKO |
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識別子 |
89671 |
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|
識別子Scheme |
KAKEN - 研究者検索 |
|
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識別子URI |
https://nrid.nii.ac.jp/ja/nrid/1000060192621/ |
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識別子 |
60192621 |
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姓名 |
鈴木, 正清 |
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言語 |
ja |
| 抄録 |
|
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内容記述タイプ |
Abstract |
|
内容記述 |
The estimation of direction-of-arrival (DOA) of signals is a basic and important problem in sensor array signal processing. To solve this problem, many algorithms have been proposed, among which the Stochastic Maximum Likelihood (SML) is one of the most concerned algorithms because of its high accuracy of DOA. However, the estimation of SML generally involves the multidimensional nonlinear optimization problem. As a result, its computational complexity is rather high. This paper addresses the issue of reducing computational complexity of SML estimation of DOA based on the Alternating Minimization (AM) algorithm. We have the following two contributions. First using transformation of matrix and properties of spatial projection, we propose an efficient AM (EAM) algorithm by dividing the SML criterion into two components. One depends on a single variable parameter while the other does not. Second when the array is a uniform linear array, we get the irreducible form of the EAM criterion (IAM) using polynomial forms. Simulation results show that both EAM and IAM can reduce the computational complexity of SML estimation greatly, while IAM is the best. Another advantage of IAM is that this algorithm can avoid the numerical instability problem which may happen in AM and EAM algorithms when more than one parameter converges to an identical value. |
|
言語 |
en |
| 書誌情報 |
en : International Journal of Antennas and Propagation
巻 2016,
p. 1-10,
発行日 2016
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| ISSN |
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収録物識別子タイプ |
PISSN |
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収録物識別子 |
1687-5869 |
| DOI |
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|
識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1155/2016/4926496 |
| 権利 |
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|
権利情報 |
Copyright c 2016 Haihua Chen et al. |
| 出版者 |
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出版者 |
Hindawi Publishing Corporation |
| 著者版フラグ |
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言語 |
en |
|
値 |
publisher |
| 出版タイプ |
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|
出版タイプ |
VoR |
|
出版タイプResource |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
Efficient AM Algorithms for Stochastic ML Estimation of DOA (1.6 MB)
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