A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks
We address the problem of DOA estimation in positioning of nodes in wireless sensor networks. The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. The SML algorithm is well-known for its high resolution of DOA estimation. However, its computational complexity is very high beca...
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ftkitamiit:oai:kitami-it.repo.nii.ac.jp:00008551 2023-05-15T16:01:57+02:00 A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks Gong, Faming Chen, Haihua Li, Shibao Liu, Jianhang Gu, Zhaozhi Suzuki, Masakiyo 2015 application/pdf https://kitami-it.repo.nii.ac.jp/record/8551/files/352012.pdf eng eng SAGE Publications https://doi.org/10.1155/2015/352012 International Journal of Distributed Sensor Networks 2015 1 11 1550-1329 https://kitami-it.repo.nii.ac.jp/record/8551/files/352012.pdf Copyright c 2015 Faming Gong et al. 2015 ftkitamiit https://doi.org/10.1155/2015/352012 2023-02-26T09:15:47Z We address the problem of DOA estimation in positioning of nodes in wireless sensor networks. The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. The SML algorithm is well-known for its high resolution of DOA estimation. However, its computational complexity is very high because multidimensional nonlinear optimization problem is usually involved. To reduce the computational complexity of SML estimation, we do the following work. (1) We point out the problems of conventional SML criterion and explain why and how these problems happen. (2) A local AM search method is proposed which could be used to find the local solution near/around the initial value. (3) We propose an algorithm which uses the local AM search method together with the estimation of DML or MUSIC as initial value to find the solution of SML. Simulation results are shown to demonstrate the effectiveness and efficiency of the proposed algorithms. In particular, the algorithm which uses the local AM method and estimation of MUSIC as initial value has much higher resolution and comparable computational complexity to MUSIC. journal article Other/Unknown Material DML Kitami Institute of Technology Repository (KIT-R) International Journal of Distributed Sensor Networks 2015 1 11 |
institution |
Open Polar |
collection |
Kitami Institute of Technology Repository (KIT-R) |
op_collection_id |
ftkitamiit |
language |
English |
description |
We address the problem of DOA estimation in positioning of nodes in wireless sensor networks. The Stochastic Maximum Likelihood (SML) algorithm is adopted in this paper. The SML algorithm is well-known for its high resolution of DOA estimation. However, its computational complexity is very high because multidimensional nonlinear optimization problem is usually involved. To reduce the computational complexity of SML estimation, we do the following work. (1) We point out the problems of conventional SML criterion and explain why and how these problems happen. (2) A local AM search method is proposed which could be used to find the local solution near/around the initial value. (3) We propose an algorithm which uses the local AM search method together with the estimation of DML or MUSIC as initial value to find the solution of SML. Simulation results are shown to demonstrate the effectiveness and efficiency of the proposed algorithms. In particular, the algorithm which uses the local AM method and estimation of MUSIC as initial value has much higher resolution and comparable computational complexity to MUSIC. journal article |
author |
Gong, Faming Chen, Haihua Li, Shibao Liu, Jianhang Gu, Zhaozhi Suzuki, Masakiyo |
spellingShingle |
Gong, Faming Chen, Haihua Li, Shibao Liu, Jianhang Gu, Zhaozhi Suzuki, Masakiyo A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
author_facet |
Gong, Faming Chen, Haihua Li, Shibao Liu, Jianhang Gu, Zhaozhi Suzuki, Masakiyo |
author_sort |
Gong, Faming |
title |
A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
title_short |
A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
title_full |
A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
title_fullStr |
A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
title_full_unstemmed |
A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
title_sort |
low computational complexity sml estimation algorithm of doa for wireless sensor networks |
publisher |
SAGE Publications |
publishDate |
2015 |
url |
https://kitami-it.repo.nii.ac.jp/record/8551/files/352012.pdf |
genre |
DML |
genre_facet |
DML |
op_relation |
https://doi.org/10.1155/2015/352012 International Journal of Distributed Sensor Networks 2015 1 11 1550-1329 https://kitami-it.repo.nii.ac.jp/record/8551/files/352012.pdf |
op_rights |
Copyright c 2015 Faming Gong et al. |
op_doi |
https://doi.org/10.1155/2015/352012 |
container_title |
International Journal of Distributed Sensor Networks |
container_volume |
2015 |
container_start_page |
1 |
op_container_end_page |
11 |
_version_ |
1766397617515790336 |