High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics
Developing the parameter estimation, particularly direction of arrival (DOA), utilizing the swarming intelligence-based flower pollination algorithm (FPA) is considered an optimistic solution. Therefore, in this paper, the features of FPA are applied for viable DOA in the case of several robust unde...
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| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2022/5876874 |
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| author | Nauman Ahmed Huigang Wang Shanshan Tu Norah A.M. Alsaif Muhammad Asif Zahoor Raja Muhammad Kashif Ammar Armghan Yasser S. Abdalla Wasiq Ali Farman Ali |
| author_facet | Nauman Ahmed Huigang Wang Shanshan Tu Norah A.M. Alsaif Muhammad Asif Zahoor Raja Muhammad Kashif Ammar Armghan Yasser S. Abdalla Wasiq Ali Farman Ali |
| author_sort | Nauman Ahmed |
| collection | DOAJ |
| description | Developing the parameter estimation, particularly direction of arrival (DOA), utilizing the swarming intelligence-based flower pollination algorithm (FPA) is considered an optimistic solution. Therefore, in this paper, the features of FPA are applied for viable DOA in the case of several robust underwater scenarios. Moreover, acoustic waves impinging from the far-field multitarget are evaluated using the different number of hydrophones of uniform linear array (ULA). The measuring parameters like robustness against noise and element quantity, estimation accuracy, computation complexity, various numbers of hydrophones, variability analysis, frequency distribution and cumulative distribution function of root mean square error (RMSE), and resolution ability are applied for analyzing the performance of the proposed model with additive white Gaussian noise (AWGN). For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. The proposed scheme for estimating the DOA generates efficient outcomes compared to the state-of-the-art algorithms over the Monte Carlo simulations. |
| format | Article |
| id | doaj-art-502c1e15898f4aef893a66caa4ec0673 |
| institution | OA Journals |
| issn | 1875-9203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-502c1e15898f4aef893a66caa4ec06732025-08-20T02:05:17ZengWileyShock and Vibration1875-92032022-01-01202210.1155/2022/5876874High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination HeuristicsNauman Ahmed0Huigang Wang1Shanshan Tu2Norah A.M. Alsaif3Muhammad Asif Zahoor Raja4Muhammad Kashif5Ammar Armghan6Yasser S. Abdalla7Wasiq Ali8Farman Ali9School of Marine Science and Technology Northwestern Polytechnical UniversitySchool of Marine Science and Technology Northwestern Polytechnical UniversityEngineering Research Center of Intelligent Perception and Autonomous ControlDepartment of PhysicsFuture Technology Research CenterDepartment of Electrical and Computer EngineeringDepartment of Electrical EngineeringDepartment of Computer Engineering and NetworksDepartment of Electrical and Computer EngineeringFaculty of Technology and EducationDeveloping the parameter estimation, particularly direction of arrival (DOA), utilizing the swarming intelligence-based flower pollination algorithm (FPA) is considered an optimistic solution. Therefore, in this paper, the features of FPA are applied for viable DOA in the case of several robust underwater scenarios. Moreover, acoustic waves impinging from the far-field multitarget are evaluated using the different number of hydrophones of uniform linear array (ULA). The measuring parameters like robustness against noise and element quantity, estimation accuracy, computation complexity, various numbers of hydrophones, variability analysis, frequency distribution and cumulative distribution function of root mean square error (RMSE), and resolution ability are applied for analyzing the performance of the proposed model with additive white Gaussian noise (AWGN). For this purpose, particle swarm optimization (PSO), minimum variance distortion-less response (MVDR), multiple signal classification (MUSIC), and estimation of signal parameter via rotational invariance technique (ESPRIT) standard counterparts are employed along with Crammer–Rao bound (CRB) to improve the worth of the proposed setup further. The proposed scheme for estimating the DOA generates efficient outcomes compared to the state-of-the-art algorithms over the Monte Carlo simulations.http://dx.doi.org/10.1155/2022/5876874 |
| spellingShingle | Nauman Ahmed Huigang Wang Shanshan Tu Norah A.M. Alsaif Muhammad Asif Zahoor Raja Muhammad Kashif Ammar Armghan Yasser S. Abdalla Wasiq Ali Farman Ali High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics Shock and Vibration |
| title | High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics |
| title_full | High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics |
| title_fullStr | High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics |
| title_full_unstemmed | High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics |
| title_short | High-Resolution Direction of Arrival Estimation of Underwater Multitargets Using Swarming Intelligence of Flower Pollination Heuristics |
| title_sort | high resolution direction of arrival estimation of underwater multitargets using swarming intelligence of flower pollination heuristics |
| url | http://dx.doi.org/10.1155/2022/5876874 |
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