MF-ANN: A Novel Artificial Neural Network-Based Method for Ocean Wind Speed Retrieval on Spaceborne GNSS-R Signal-Reference-Cited by-同舟云学术

MF-ANN: A Novel Artificial Neural Network-Based Method for Ocean Wind Speed Retrieval on Spaceborne GNSS-R Signal

Published:2023 Issue: Volume:61 Page:1-17
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Xie Heng¹^ORCID,Cheng Xing¹^ORCID,He Shanbao¹^ORCID,Li Yujie¹^ORCID,Pang Jingjing²^ORCID,Li Shuaishuai²^ORCID

Affiliation:

1. School of Information and Communication Engineering, Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument, Beijing Information Science and Technology University, Beijing, China

2. School of Information and Communication Engineering, Beijing Information Science and Technology University, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10278224.pdf?arnumber=10278224

Reference47 articles.

1. Spaceborne GNSS-R Minimum Variance Wind Speed Estimator

2. Exploiting the ANN Potential in Estimating Snow Depth and Snow Water Equivalent From the Airborne SnowSAR Data at X- and Ku-Bands

3. Wind Speed Retrieval Algorithm for the Cyclone Global Navigation Satellite System (CYGNSS) Mission

4. XGBoost

5. A hybrid of deep learning and hand-crafted features based approach for snow cover mapping

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