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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-01-01
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| Series: | International Journal of Antennas and Propagation |
| Online Access: | http://dx.doi.org/10.1155/2019/3858794 |
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| author | Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki |
| author_facet | Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki |
| author_sort | Haihua Chen |
| collection | DOAJ |
| 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 |
| id | doaj-art-2a1810cf006e4770b5842a6ba6427e7d |
| institution | Kabale University |
| issn | 1687-5869 1687-5877 |
| language | English |
| publishDate | 2019-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Antennas and Propagation |
| spelling | doaj-art-2a1810cf006e4770b5842a6ba6427e7d2025-02-03T05:59:41ZengWileyInternational Journal of Antennas and Propagation1687-58691687-58772019-01-01201910.1155/2019/38587943858794General Improvements of Heuristic Algorithms for Low Complexity DOA EstimationHaihua Chen0Haoran Li1Mingyang Yang2Changbo Xiang3Masakiyo Suzuki4College of Ocean and Spatial Information, China University of Petroleum, Qingdao, Shandong 266580, ChinaBeijing Key Laboratory of Mobile Computing and Pervasive Device, Institute of Computing Technology, Chinese Academy of Science, Beijing, ChinaNational Key Laboratory of Science and Technology on Electronic Test and Measurement, The 41st Research Institute of China Electronic Science and Technology Group Corporation, Qingdao, ChinaNational Key Laboratory of Science and Technology on Electronic Test and Measurement, The 41st Research Institute of China Electronic Science and Technology Group Corporation, Qingdao, ChinaGraduate School of Engineering, Kitami Institute of Technology, Kitami, Hokkaido 090–8507, JapanHeuristic 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.http://dx.doi.org/10.1155/2019/3858794 |
| spellingShingle | Haihua Chen Haoran Li Mingyang Yang Changbo Xiang Masakiyo Suzuki General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation International Journal of Antennas and Propagation |
| title | 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_short | General Improvements of Heuristic Algorithms for Low Complexity DOA Estimation |
| title_sort | general improvements of heuristic algorithms for low complexity doa estimation |
| url | http://dx.doi.org/10.1155/2019/3858794 |
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