Control of pulse format in high energy per pulse all-fiber erbium/ytterbium laser systems

2017 ◽  
Author(s):  
Michael Klopfer ◽  
Matthew K. Block ◽  
James Deffenbaugh ◽  
Zak G. Fitzpatrick ◽  
Michael T. Urioste ◽  
...  
Keyword(s):  
2021 ◽  
Vol 30 (10) ◽  
pp. 22-27
Author(s):  
Ho Jin MA ◽  
Ha-Neul KIM

Solid-state lasers have aroused many researchers’ interests for a variety of applications in military and industrial fields. Because of the preference for increased output power, Nd:YAG single crystals, which are the most widely used gain media, should be replaced by other more suitable candidates. Polycrystalline sesquioxide ceramics show great potential for use as gain media because their thermal and mechanical characteristics are suitable for use with high-energy laser systems. Recently, novel concepts of the gain media were also introduced. Herein, while briefly looking back on the progress of polycrystalline laser ceramics, we will discuss new interests in host materials and systems.


2017 ◽  
Author(s):  
Karel Nejezchleb ◽  
Jan Kubát ◽  
Jan Šulc ◽  
Helena Jelínková

2020 ◽  
Vol 8 (4) ◽  
pp. 334-363 ◽  
Author(s):  
Christopher C. Surma ◽  
Martin Barczyk

This article develops and implements a vision-based unmanned aerial vehicle (UAV)-to-UAV pursuit system using a commercial off-the-shelf Parrot AR.Drone 2.0 quadrotor. This technology is intended as a countermeasure to rogue drones carrying out activities such as flying in restricted airspace, performing unauthorized aerial videography, transporting contraband and other criminal activities, or being used as improvised weapons. The proposed approach offers benefits over other current solutions, such as wide-area radio-frequency jamming that interferes with regular communication devices or high-energy military laser systems that are expensive and time consuming to set up. A linear dynamics model of the AR.Drone 2.0 vehicle stabilized by its onboard feedback control system is derived, and its parameters are experimentally identified. A linear model predictive control is developed to track specified flight trajectories, then implemented and validated in hardware flight tests. Detection and ranging of the target UAV from the pursuer UAV’s onboard monocular camera are performed using the YOLO v2 convolutional neural network algorithm. The combined control and vision design is implemented in hardware and tested quantitatively in flight experiments.


2015 ◽  
Vol 22 (4) ◽  
pp. 043302 ◽  
Author(s):  
A. Bartnik ◽  
P. Wachulak ◽  
T. Fok ◽  
Ł. Węgrzyński ◽  
H. Fiedorowicz ◽  
...  

2016 ◽  
Vol 1 (3) ◽  
pp. 425-443 ◽  
Author(s):  
Y. Sakawa ◽  
T. Morita ◽  
Y. Kuramitsu ◽  
H. Takabe

2005 ◽  
Author(s):  
Richard J. Bartell ◽  
Glen P. Perram ◽  
Steven T. Fiorino ◽  
Scott N. Long ◽  
Marken J. Houle ◽  
...  

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