Direction of arrival estimation of airborne multiple‐input multiple‐output radar in multipath environment Article Swipe
Yili Hu
,
Yongbo Zhao
,
Sheng Chen
,
Xiaojiao Pang
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1049/rsn2.12099
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1049/rsn2.12099
Airborne multiple‐input multiple‐output (MIMO) radar can transmit orthogonal waveforms to increase the range of the detection target. However, in a multipath environment, airborne MIMO radar also has energy radiated to the target through multipath directions, which makes the multipath phenomenon of airborne MIMO radar complicated. Because the direct path signal and the multipath signals of the airborne radar are at different range gates, the characteristics of data between the direct path signal and the multipath signals of the airborne MIMO radar can be used to propose a method for estimating the reflection coefficient amplitude (RCA). Considering that the target echoes data at different range gates can be used to estimate the elevation angle of the target, a direction of arrival (DOA) estimation method using data fusion at low signal‐to‐noise ratio (SNR) is proposed. Moreover, at high SNR, the signal path corresponding to the maximum target echo power is selected for DOA estimation based on the estimated multipath RCA. The proposed method makes full use of all target echo data of airborne MIMO radar in a multipath environment and is suitable for practical applications. Finally, simulation experiments verify that the proposed method can effectively improve the DOA estimation accuracy.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1049/rsn2.12099
- OA Status
- gold
- Cited By
- 2
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3171764476
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3171764476Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1049/rsn2.12099Digital Object Identifier
- Title
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Direction of arrival estimation of airborne multiple‐input multiple‐output radar in multipath environmentWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-06-09Full publication date if available
- Authors
-
Yili Hu, Yongbo Zhao, Sheng Chen, Xiaojiao PangList of authors in order
- Landing page
-
https://doi.org/10.1049/rsn2.12099Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1049/rsn2.12099Direct OA link when available
- Concepts
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Multipath propagation, Radar, Computer science, Remote sensing, Estimation, Radar signal processing, Environmental science, Geology, Telecommunications, Engineering, Signal processing, Channel (broadcasting), Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
2Total citation count in OpenAlex
- Citations by year (recent)
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2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
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23Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.can | 6, 82, 106, 192 |
| abstract_inverted_index.for | 89, 150, 181 |
| abstract_inverted_index.has | 27 |
| abstract_inverted_index.low | 128 |
| abstract_inverted_index.the | 12, 15, 31, 38, 47, 52, 56, 64, 69, 74, 78, 91, 98, 111, 115, 138, 143, 155, 189, 195 |
| abstract_inverted_index.use | 164 |
| abstract_inverted_index.MIMO | 24, 43, 80, 172 |
| abstract_inverted_index.RCA. | 158 |
| abstract_inverted_index.SNR, | 137 |
| abstract_inverted_index.also | 26 |
| abstract_inverted_index.data | 67, 101, 125, 169 |
| abstract_inverted_index.echo | 146, 168 |
| abstract_inverted_index.full | 163 |
| abstract_inverted_index.high | 136 |
| abstract_inverted_index.path | 49, 71, 140 |
| abstract_inverted_index.that | 97, 188 |
| abstract_inverted_index.used | 84, 108 |
| abstract_inverted_index.(DOA) | 121 |
| abstract_inverted_index.(SNR) | 131 |
| abstract_inverted_index.angle | 113 |
| abstract_inverted_index.based | 153 |
| abstract_inverted_index.gates | 105 |
| abstract_inverted_index.makes | 37, 162 |
| abstract_inverted_index.power | 147 |
| abstract_inverted_index.radar | 5, 25, 44, 58, 81, 173 |
| abstract_inverted_index.range | 13, 62, 104 |
| abstract_inverted_index.ratio | 130 |
| abstract_inverted_index.using | 124 |
| abstract_inverted_index.which | 36 |
| abstract_inverted_index.(MIMO) | 4 |
| abstract_inverted_index.(RCA). | 95 |
| abstract_inverted_index.direct | 48, 70 |
| abstract_inverted_index.echoes | 100 |
| abstract_inverted_index.energy | 28 |
| abstract_inverted_index.fusion | 126 |
| abstract_inverted_index.gates, | 63 |
| abstract_inverted_index.method | 88, 123, 161, 191 |
| abstract_inverted_index.signal | 50, 72, 139 |
| abstract_inverted_index.target | 32, 99, 145, 167 |
| abstract_inverted_index.verify | 187 |
| abstract_inverted_index.Because | 46 |
| abstract_inverted_index.arrival | 120 |
| abstract_inverted_index.between | 68 |
| abstract_inverted_index.improve | 194 |
| abstract_inverted_index.maximum | 144 |
| abstract_inverted_index.propose | 86 |
| abstract_inverted_index.signals | 54, 76 |
| abstract_inverted_index.target, | 116 |
| abstract_inverted_index.target. | 17 |
| abstract_inverted_index.through | 33 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Airborne | 1 |
| abstract_inverted_index.Finally, | 184 |
| abstract_inverted_index.However, | 18 |
| abstract_inverted_index.airborne | 23, 42, 57, 79, 171 |
| abstract_inverted_index.estimate | 110 |
| abstract_inverted_index.increase | 11 |
| abstract_inverted_index.proposed | 160, 190 |
| abstract_inverted_index.radiated | 29 |
| abstract_inverted_index.selected | 149 |
| abstract_inverted_index.suitable | 180 |
| abstract_inverted_index.transmit | 7 |
| abstract_inverted_index.Moreover, | 134 |
| abstract_inverted_index.accuracy. | 198 |
| abstract_inverted_index.amplitude | 94 |
| abstract_inverted_index.detection | 16 |
| abstract_inverted_index.different | 61, 103 |
| abstract_inverted_index.direction | 118 |
| abstract_inverted_index.elevation | 112 |
| abstract_inverted_index.estimated | 156 |
| abstract_inverted_index.multipath | 21, 34, 39, 53, 75, 157, 176 |
| abstract_inverted_index.practical | 182 |
| abstract_inverted_index.proposed. | 133 |
| abstract_inverted_index.waveforms | 9 |
| abstract_inverted_index.estimating | 90 |
| abstract_inverted_index.estimation | 122, 152, 197 |
| abstract_inverted_index.orthogonal | 8 |
| abstract_inverted_index.phenomenon | 40 |
| abstract_inverted_index.reflection | 92 |
| abstract_inverted_index.simulation | 185 |
| abstract_inverted_index.Considering | 96 |
| abstract_inverted_index.coefficient | 93 |
| abstract_inverted_index.directions, | 35 |
| abstract_inverted_index.effectively | 193 |
| abstract_inverted_index.environment | 177 |
| abstract_inverted_index.experiments | 186 |
| abstract_inverted_index.complicated. | 45 |
| abstract_inverted_index.environment, | 22 |
| abstract_inverted_index.applications. | 183 |
| abstract_inverted_index.corresponding | 141 |
| abstract_inverted_index.characteristics | 65 |
| abstract_inverted_index.multiple‐input | 2 |
| abstract_inverted_index.multiple‐output | 3 |
| abstract_inverted_index.signal‐to‐noise | 129 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5012445708 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I149594827 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8899999856948853 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.78790471 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |