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: Haihua Chen, Haoran Li, Mingyang Yang, Changbo Xiang, Masakiyo Suzuki
Format: Article
Language:English
Published: Wiley 2019-01-01
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.
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institution Kabale University
issn 1687-5869
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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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AT haoranli generalimprovementsofheuristicalgorithmsforlowcomplexitydoaestimation
AT mingyangyang generalimprovementsofheuristicalgorithmsforlowcomplexitydoaestimation
AT changboxiang generalimprovementsofheuristicalgorithmsforlowcomplexitydoaestimation
AT masakiyosuzuki generalimprovementsofheuristicalgorithmsforlowcomplexitydoaestimation