Characterization of micro-Doppler radar signature of commercial wind turbines

2014 ◽  
Author(s):  
Fanxing Kong ◽  
Yan Zhang ◽  
Robert Palmer
Keyword(s):  
Wind Turbines ◽  
Doppler Radar ◽  
Radar Signature

scholarly journals Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3937
Author(s):  
Seungeon Song ◽  
Bongseok Kim ◽  
Sangdong Kim ◽  
Jonghun Lee
Keyword(s):  
Deep Learning ◽  
Gesture Recognition ◽  
Smart Home ◽  
Doppler Radar ◽  
Radar Images ◽  
Radar Signature ◽  
Memory Efficiency ◽  
High Compression ◽  
Value Decomposition ◽  
Deep Learning Model

Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar’s inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.

The accuracy and predictability of micro Doppler radar signature projection algorithm measuring functional movement in NCAA athletes

2021 ◽  
Vol 85 ◽  
pp. 96-102
Author(s):  
Cayce Onks ◽  
Donald Hall ◽  
Tyler Ridder ◽  
Zacharie Idriss ◽  
Joseph Andrie ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Projection Algorithm ◽  
Functional Movement ◽  
Radar Signature ◽  
Ncaa Athletes

scholarly journals Characterization of aerodynamic performance of ducted wind turbines: A numerical study

Wind Energy ◽  
2019 ◽  
Vol 22 (12) ◽  
pp. 1655-1666 ◽  
Author(s):  
Vinit V. Dighe ◽  
Gael Oliveira ◽  
Francesco Avallone ◽  
Gerard J. W. Bussel
Keyword(s):  
Wind Turbines ◽  
Numerical Study ◽  
Aerodynamic Performance

Modeling the Radar Signature of Raindrops in Aircraft Wake Vortices

2013 ◽  
Vol 30 (3) ◽  
pp. 470-484 ◽  
Author(s):  
Zhongxun Liu ◽  
Nicolas Jeannin ◽  
Francois Vincent ◽  
Xuesong Wang
Keyword(s):  
Traffic Control ◽  
Vortex Flow ◽  
Doppler Radar ◽  
Elevation Angle ◽  
Wake Vortex ◽  
Wake Vortices ◽  
Radar Signature ◽  
Radar Echo ◽  
Aircraft Wake ◽  
Resolution Cell

Abstract The present work is dedicated to the modeling and simulation of the radar signature of raindrops within wake vortices. This is achieved through the computation of the equation of raindrop motion within the wake vortex flow. Based on the inhomogeneous distribution of raindrops within wake vortices, the radar echo model is computed for raindrops in a given resolution cell. Simulated Doppler radar signatures of raindrops within wake vortices are shown to be a potential criterion for identifying wake vortex hazards in air traffic control. The dependence of the radar signature on various parameters, including the radial resolution and antenna elevation angle, is also analyzed.

Pulsed Vulcanian explosions: A characterization of eruption dynamics using Doppler radar

Geology ◽  
2015 ◽  
Vol 43 (11) ◽  
pp. 995-998 ◽  
Author(s):  
Lea Scharff ◽  
Matthias Hort ◽  
Nick R. Varley
Keyword(s):  
Doppler Radar ◽  
Eruption Dynamics ◽  
Vulcanian Explosions

scholarly journals Characterization of a new open jet wind tunnel to optimize and test vertical axis wind turbines

2017 ◽  
Vol 9 (3) ◽  
pp. 033302 ◽  
Author(s):  
Silvana Tourn ◽  
Jordi Pallarès ◽  
Ildefonso Cuesta ◽  
Uwe Schmidt Paulsen
Keyword(s):  
Wind Tunnel ◽  
Wind Turbines ◽  
Vertical Axis ◽  
Vertical Axis Wind Turbines

scholarly journals GoWInD: Wind Energy Spatiotemporal Assessment and Characterization of End-of-Life Activities

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6015
Author(s):  
Francisco Haces-Fernandez
Keyword(s):  
United States ◽  
Wind Energy ◽  
End Of Life ◽  
Wind Turbines ◽  
The United States ◽  
Temporal And Spatial Distribution ◽  
Continuous Growth ◽  
Disposal Options ◽  
Life Options

Concerns on the lack sustainable end-of-life options for wind turbines have significantly increased in recent years. To ensure wind energy continuous growth, this research develops a novel spatiotemporal methodology that sustainably handles end-of-life activities for wind equipment. This research introduces the Global Wind Inventory for Future Decommissioning (GoWInD), which assesses and characterizes wind turbines according to individual spatiotemporal decommissioning and sustainability attributes. Applying data from GoWInD, the research developments networks of end-of-life (EoL) centers for wind turbines. The placement and operational levels of EoL centers optimize sustainable decommissioning according to changing spatiotemporal features of wind turbines. The methodology was evaluated for the United States, developing the United States Global Wind Inventory for Future Decommissioning (US—GoWInD), implementing the network of United States end-of-life (US—EoL) centers. Significant imbalances on the temporal and spatial distribution of US wind decommissioning inventory were revealed by the system. Diverse options to effectively handle these imbalances were highlighted by the methodology, including US—EoL center optimization according to placement, operational levels and potential complementarities. Particular attention was paid to components with challenging disposal options. The system can be implemented for diverse geographical locations and alternative spatial and temporal resolutions.

Short-Range Doppler-Radar Signatures from Industrial Wind Turbines: Theory, Simulations, and Measurements

2016 ◽  
Vol 65 (9) ◽  
pp. 2108-2119 ◽  
Author(s):  
Jose-Maria Munoz-Ferreras ◽  
Zhengyu Peng ◽  
Yao Tang ◽  
Roberto Gomez-Garcia ◽  
Daan Liang ◽  
...  
Keyword(s):  
Wind Turbines ◽  
Short Range ◽  
Doppler Radar ◽  
Radar Signatures
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