Beamforming against main lobe interference based on radial basis function neural network Article Swipe
Shuai Wang
,
Jianjun Xiang
,
Peng Fang
,
Zhijun Li
,
Haoyang Li
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2031/1/012061
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2031/1/012061
Aiming at the problem that the performance of traditional beamforming algorithm deteriorates sharply in the presence of main lobe interference, a beamforming algorithm based on radial basis function (RBF) neural network is proposed. Firstly, the minimum variance distortionless response (MVDR) is used to solve the optimal beam pattern in the presence of side lobe interference. Then, the training set of RBF neural network is constructed according to the optimal beam pattern and the direction information of main lobe interference to train the network, so that the trained RBF neural network can suppress the main lobe interference while maintaining the ability of optimal beamforming. The simulation results show that the method can overcome the limitations of traditional beamforming algorithm, suppress the main lobe interference and side lobe interference, and form the correct beam direction. At the same time, the algorithm also has good real-time performance.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2031/1/012061
- OA Status
- diamond
- Cited By
- 2
- References
- 7
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3203883514
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3203883514Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/2031/1/012061Digital Object Identifier
- Title
-
Beamforming against main lobe interference based on radial basis function neural networkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-09-01Full publication date if available
- Authors
-
Shuai Wang, Jianjun Xiang, Peng Fang, Zhijun Li, Haoyang LiList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2031/1/012061Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1088/1742-6596/2031/1/012061Direct OA link when available
- Concepts
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Beamforming, Main lobe, Side lobe, Interference (communication), Computer science, Artificial neural network, Lobe, Radial basis function, Algorithm, Artificial intelligence, Telecommunications, Channel (broadcasting), Anatomy, Antenna (radio), MedicineTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1Per-year citation counts (last 5 years)
- References (count)
-
7Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.and | 72, 124, 128 |
| abstract_inverted_index.can | 91, 111 |
| abstract_inverted_index.has | 141 |
| abstract_inverted_index.set | 59 |
| abstract_inverted_index.the | 3, 6, 15, 35, 45, 50, 57, 68, 73, 82, 86, 93, 99, 109, 113, 120, 130, 135, 138 |
| abstract_inverted_index.also | 140 |
| abstract_inverted_index.beam | 47, 70, 132 |
| abstract_inverted_index.form | 129 |
| abstract_inverted_index.good | 142 |
| abstract_inverted_index.lobe | 19, 54, 78, 95, 122, 126 |
| abstract_inverted_index.main | 18, 77, 94, 121 |
| abstract_inverted_index.same | 136 |
| abstract_inverted_index.show | 107 |
| abstract_inverted_index.side | 53, 125 |
| abstract_inverted_index.that | 5, 85, 108 |
| abstract_inverted_index.used | 42 |
| abstract_inverted_index.(RBF) | 29 |
| abstract_inverted_index.Then, | 56 |
| abstract_inverted_index.based | 24 |
| abstract_inverted_index.basis | 27 |
| abstract_inverted_index.solve | 44 |
| abstract_inverted_index.time, | 137 |
| abstract_inverted_index.train | 81 |
| abstract_inverted_index.while | 97 |
| abstract_inverted_index.(MVDR) | 40 |
| abstract_inverted_index.Aiming | 1 |
| abstract_inverted_index.method | 110 |
| abstract_inverted_index.neural | 30, 62, 89 |
| abstract_inverted_index.radial | 26 |
| abstract_inverted_index.ability | 100 |
| abstract_inverted_index.correct | 131 |
| abstract_inverted_index.minimum | 36 |
| abstract_inverted_index.network | 31, 63, 90 |
| abstract_inverted_index.optimal | 46, 69, 102 |
| abstract_inverted_index.pattern | 48, 71 |
| abstract_inverted_index.problem | 4 |
| abstract_inverted_index.results | 106 |
| abstract_inverted_index.sharply | 13 |
| abstract_inverted_index.trained | 87 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Firstly, | 34 |
| abstract_inverted_index.function | 28 |
| abstract_inverted_index.network, | 83 |
| abstract_inverted_index.overcome | 112 |
| abstract_inverted_index.presence | 16, 51 |
| abstract_inverted_index.response | 39 |
| abstract_inverted_index.suppress | 92, 119 |
| abstract_inverted_index.training | 58 |
| abstract_inverted_index.variance | 37 |
| abstract_inverted_index.according | 66 |
| abstract_inverted_index.algorithm | 11, 23, 139 |
| abstract_inverted_index.direction | 74 |
| abstract_inverted_index.proposed. | 33 |
| abstract_inverted_index.real-time | 143 |
| abstract_inverted_index.algorithm, | 118 |
| abstract_inverted_index.direction. | 133 |
| abstract_inverted_index.simulation | 105 |
| abstract_inverted_index.beamforming | 10, 22, 117 |
| abstract_inverted_index.constructed | 65 |
| abstract_inverted_index.information | 75 |
| abstract_inverted_index.limitations | 114 |
| abstract_inverted_index.maintaining | 98 |
| abstract_inverted_index.performance | 7 |
| abstract_inverted_index.traditional | 9, 116 |
| abstract_inverted_index.beamforming. | 103 |
| abstract_inverted_index.deteriorates | 12 |
| abstract_inverted_index.interference | 79, 96, 123 |
| abstract_inverted_index.performance. | 144 |
| abstract_inverted_index.interference, | 20, 127 |
| abstract_inverted_index.interference. | 55 |
| abstract_inverted_index.distortionless | 38 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile.value | 0.46647902 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |