CA3225182A1 - Apprentissage profond pour la prediction d'affaiblissement de pluie dans des communications par satellite - Google Patents
Apprentissage profond pour la prediction d'affaiblissement de pluie dans des communications par satellite Download PDFInfo
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- CA3225182A1 CA3225182A1 CA3225182A CA3225182A CA3225182A1 CA 3225182 A1 CA3225182 A1 CA 3225182A1 CA 3225182 A CA3225182 A CA 3225182A CA 3225182 A CA3225182 A CA 3225182A CA 3225182 A1 CA3225182 A1 CA 3225182A1
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- 238000013135 deep learning Methods 0.000 title claims abstract description 34
- 238000004891 communication Methods 0.000 title description 6
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Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/14—Relay systems
- H04B7/15—Active relay systems
- H04B7/185—Space-based or airborne stations; Stations for satellite systems
- H04B7/1851—Systems using a satellite or space-based relay
- H04B7/18513—Transmission in a satellite or space-based system
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
- G06N3/0442—Recurrent networks, e.g. Hopfield networks characterised by memory or gating, e.g. long short-term memory [LSTM] or gated recurrent units [GRU]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/048—Activation functions
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Software Systems (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Mathematical Physics (AREA)
- Evolutionary Computation (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Astronomy & Astrophysics (AREA)
- Radar Systems Or Details Thereof (AREA)
- Image Processing (AREA)
Abstract
La prédiction d'affaiblissement de pluie pour une zone de pluie à l'aide d'un système d'apprentissage profond peut comprendre : la formation d'un réseau de neurones artificiels (NN) par importation dans le NN d'un ensemble de formation d'informations d'image et d'informations de balise, les informations d'image comprenant des ensembles de données d'image comprenant une vue en nuage d'une zone d'intérêt (AoI), une géolocalisation et une horodate, et les informations de balise comprenant des ensembles de données de balise comprenant une intensité de balise, un état d'affaiblissement de pluie actuel, une géolocalisation et une horodate ; le pré-traitement pour homogénéiser et pour extraire des données de correspondance spatiale et temporelle pour l'AoI à partir d'une information d'image en direct et d'une information de balise en direct ; et la prévision d'un affaiblissement de pluie sur la base des données dans un futur proche. La géolocalisation d'un ou plusieurs des ensembles de données de balise est située à l'intérieur de l'AoI, et la périodicité des informations de balise en direct et des informations d'image en direct est inférieure ou égale à cinq (5) minutes.
Applications Claiming Priority (5)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US202163203351P | 2021-07-19 | 2021-07-19 | |
| US63/203,351 | 2021-07-19 | ||
| US17/453,258 US20230019771A1 (en) | 2021-07-19 | 2021-11-02 | Deep Learning for Rain Fade Prediction in Satellite Communications |
| US17/453,258 | 2021-11-02 | ||
| PCT/US2022/073767 WO2023004260A1 (fr) | 2021-07-19 | 2022-07-15 | Apprentissage profond pour la prédiction d'affaiblissement de pluie dans des communications par satellite |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CA3225182A1 true CA3225182A1 (fr) | 2023-01-26 |
Family
ID=82932531
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA3225182A Pending CA3225182A1 (fr) | 2021-07-19 | 2022-07-15 | Apprentissage profond pour la prediction d'affaiblissement de pluie dans des communications par satellite |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4374506A1 (fr) |
| CA (1) | CA3225182A1 (fr) |
| WO (1) | WO2023004260A1 (fr) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116073893B (zh) * | 2023-04-06 | 2023-07-18 | 西安空间无线电技术研究所 | 标定多频段毫米波信号大气传输特性的载荷系统及方法 |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10938652B1 (en) * | 2019-08-20 | 2021-03-02 | Hughes Network Systems, Llc | Gateway diversity switching |
-
2022
- 2022-07-15 EP EP22755037.3A patent/EP4374506A1/fr active Pending
- 2022-07-15 WO PCT/US2022/073767 patent/WO2023004260A1/fr active Application Filing
- 2022-07-15 CA CA3225182A patent/CA3225182A1/fr active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023004260A1 (fr) | 2023-01-26 |
| EP4374506A1 (fr) | 2024-05-29 |
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