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...
Published in: | International Journal of Distributed Sensor Networks |
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ftdoajarticles:oai:doaj.org/article:6d8cd5ed76bb47b1b0f0c0ba1bf54c4a 2023-10-09T21:51:03+02:00 A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks Faming Gong Haihua Chen Shibao Li Jianhang Liu Zhaozhi Gu Masakiyo Suzuki 2015-10-01T00:00:00Z https://doi.org/10.1155/2015/352012 https://doaj.org/article/6d8cd5ed76bb47b1b0f0c0ba1bf54c4a EN eng Hindawi - SAGE Publishing https://doi.org/10.1155/2015/352012 https://doaj.org/toc/1550-1477 1550-1477 doi:10.1155/2015/352012 https://doaj.org/article/6d8cd5ed76bb47b1b0f0c0ba1bf54c4a International Journal of Distributed Sensor Networks, Vol 11 (2015) Electronic computers. Computer science QA75.5-76.95 article 2015 ftdoajarticles https://doi.org/10.1155/2015/352012 2023-09-10T00:51:23Z 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. Article in Journal/Newspaper DML Directory of Open Access Journals: DOAJ Articles International Journal of Distributed Sensor Networks 2015 1 11 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Electronic computers. Computer science QA75.5-76.95 |
spellingShingle |
Electronic computers. Computer science QA75.5-76.95 Faming Gong Haihua Chen Shibao Li Jianhang Liu Zhaozhi Gu Masakiyo Suzuki A Low Computational Complexity SML Estimation Algorithm of DOA for Wireless Sensor Networks |
topic_facet |
Electronic computers. Computer science QA75.5-76.95 |
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. |
format |
Article in Journal/Newspaper |
author |
Faming Gong Haihua Chen Shibao Li Jianhang Liu Zhaozhi Gu Masakiyo Suzuki |
author_facet |
Faming Gong Haihua Chen Shibao Li Jianhang Liu Zhaozhi Gu Masakiyo Suzuki |
author_sort |
Faming Gong |
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 |
Hindawi - SAGE Publishing |
publishDate |
2015 |
url |
https://doi.org/10.1155/2015/352012 https://doaj.org/article/6d8cd5ed76bb47b1b0f0c0ba1bf54c4a |
genre |
DML |
genre_facet |
DML |
op_source |
International Journal of Distributed Sensor Networks, Vol 11 (2015) |
op_relation |
https://doi.org/10.1155/2015/352012 https://doaj.org/toc/1550-1477 1550-1477 doi:10.1155/2015/352012 https://doaj.org/article/6d8cd5ed76bb47b1b0f0c0ba1bf54c4a |
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_ |
1779314153456926720 |