General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation
Heuristic algorithms are considered to be effective approaches for super-resolution DOA estimations such as Deterministic Maximum Likelihood (DML), Stochastic Maximum Likelihood (SML), and Weighted Subspace Fitting (WSF) which are involved in nonlinear multi-dimensional optimization. Traditional heu...
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fthindawi:oai:hindawi.com:10.1155/2019/3858794 2023-05-15T16:01:49+02:00 General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki 2019 https://doi.org/10.1155/2019/3858794 en eng International Journal of Antennas and Propagation https://doi.org/10.1155/2019/3858794 Copyright © 2019 Haihua Chen et al. Research Article 2019 fthindawi https://doi.org/10.1155/2019/3858794 2019-12-12T15:48:00Z Heuristic algorithms are considered to be effective approaches for super-resolution DOA estimations such as Deterministic Maximum Likelihood (DML), Stochastic Maximum Likelihood (SML), and Weighted Subspace Fitting (WSF) which are involved in nonlinear multi-dimensional optimization. Traditional heuristic algorithms usually need a large number of particles and iteration times. As a result, the computational complexity is still a bit high, which prevents the application of these super-resolution techniques in real systems. To reduce the computational complexity of heuristic algorithms for these super-resolution techniques of DOA, this paper proposes three general improvements of heuristic algorithms, i.e., the optimization of the initialization space, the optimization of evolutionary strategies, and the usage of parallel computing techniques. Simulation results show that the computational complexity can be greatly reduced while these improvements are used. Article in Journal/Newspaper DML Hindawi Publishing Corporation International Journal of Antennas and Propagation 2019 1 9 |
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Open Polar |
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Hindawi Publishing Corporation |
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fthindawi |
language |
English |
description |
Heuristic algorithms are considered to be effective approaches for super-resolution DOA estimations such as Deterministic Maximum Likelihood (DML), Stochastic Maximum Likelihood (SML), and Weighted Subspace Fitting (WSF) which are involved in nonlinear multi-dimensional optimization. Traditional heuristic algorithms usually need a large number of particles and iteration times. As a result, the computational complexity is still a bit high, which prevents the application of these super-resolution techniques in real systems. To reduce the computational complexity of heuristic algorithms for these super-resolution techniques of DOA, this paper proposes three general improvements of heuristic algorithms, i.e., the optimization of the initialization space, the optimization of evolutionary strategies, and the usage of parallel computing techniques. Simulation results show that the computational complexity can be greatly reduced while these improvements are used. |
format |
Article in Journal/Newspaper |
author |
Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki |
spellingShingle |
Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
author_facet |
Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki |
author_sort |
Haihua Chen |
title |
General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
title_short |
General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
title_full |
General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
title_fullStr |
General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
title_full_unstemmed |
General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
title_sort |
general improvements of heuristic algorithms for low complexity doa estimation |
publisher |
International Journal of Antennas and Propagation |
publishDate |
2019 |
url |
https://doi.org/10.1155/2019/3858794 |
genre |
DML |
genre_facet |
DML |
op_relation |
https://doi.org/10.1155/2019/3858794 |
op_rights |
Copyright © 2019 Haihua Chen et al. |
op_doi |
https://doi.org/10.1155/2019/3858794 |
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International Journal of Antennas and Propagation |
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2019 |
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1 |
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9 |
_version_ |
1766397529452183552 |