Identifying and Exploiting Vulnerabilities in Civilian Unmanned Aerial Vehicle Systems and Evaluating and Countering Potential Threats Against the United States Airspace

Author(s):  
Philip J. Costello
2015 ◽  
Vol 16 (2) ◽  
Author(s):  
Egalita Irfan

Unmanned Aerial Vehicle (UAV) is an armed unmanned plane, which is also one of the most advanced technologies developed by the United States. UAV is more superior compared with other kinds of weapon. Currently, it is used in many parts of the world as a part of the United States' counter-terrorism measure. However, the use of UAV in Pakistan since 2004 to 2012 does not successfully reduce the number of terrorist attack that happens on that country. This research aims to figure out the reasons behind this failure through the use of congruence in retrospective. The results show that the failure of UAV relies upon 3 factors: (1) US did not really understand the characteristic of targeted terrorist organizations, (2) there is a mistake in the decision making based on the intelligence cycle, and (3) the nonexistent of local society's support.


2013 ◽  
Vol 01 (02) ◽  
pp. 199-209 ◽  
Author(s):  
Kimberly Jackson ◽  
Justine Li ◽  
Eric Timmons ◽  
Jason Wallace

From September 2011 through May 2012, icarusLabs competed in the UAVForge Competition, sponsored by the United States Defense Advanced Research Projects Agency (DARPA). The objective of the competition was to design and build a small unmanned aerial vehicle (UAV) that could complete a local surveillance mission. A unique feature of the competition was an experimental crowdsourcing model, in which competing teams were able to provide technical feedback to each other as part of the design process. The icarusLabs team's solution to the challenge combined a tricopter and blended wing body aircraft into a single hybrid airframe. This paper presents the rationale and theory behind the design as well as the lessons learned from the technical and logistical challenges faced. In addition, the authors reflect on the crowdsourcing aspect of the challenge from a competitor's perspective. Overall, incentives for individual teams' success directly conflicted with the essence of crowdsourcing, but the competition was successful at stimulating interest to fill a void in current UAV solutions, bringing together passionate individuals from the global unmanned systems community, and generating a broad range of novel approaches to address the presented challenges.


Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 716 ◽  
Author(s):  
Hugh Z. Li ◽  
Mumbi Mundia-Howe ◽  
Matthew D. Reeder ◽  
Natalie J. Pekney

The United States Environmental Protection Agency Greenhouse Gas Inventory only recently updated the emission factors of natural gas gathering pipelines in April 2019 from the previous estimates based on a 1990s study of distribution pipelines. Additional measurements are needed from different basins for more accurate assessments of methane emissions from natural gas midstream industries and hence the overall climate implications of natural gas as the interim major energy source for the next decade. We conducted an unmanned aerial vehicle (UAV) survey and a ground-based vehicle sampling campaign targeting gathering pipeline systems in the Utica Shale from March to April in 2019. Out of 73 km of pipeline systems surveyed, we found no leaks on pipelines and two leaks on an accessory block valve with leak rates of 3.8 ± 0.4 and 7.6 ± 0.8 mg/s. The low leak frequency phenomenon was also observed in the only existing gathering pipeline study in Fayetteville Shale. The UAV sampling system facilitated ease of access, broadened the availability of pipelines for leak detection, and was estimated to detect methane leaks down to 0.07 g/s using Gaussian dispersion modeling. For future UAV surveys adopting similar instrument setup and dispersion models, we recommend arranging controlled release experiments first to understand the system’s detection limit and choosing sampling days with steady and low wind speeds (2 m/s).


2019 ◽  
Vol 27 (2) ◽  
pp. 61-69 ◽  
Author(s):  
Timothy B. Nysetvold ◽  
John L. Salmon

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 168671-168710 ◽  
Author(s):  
Honggu Kang ◽  
Jingon Joung ◽  
Jinyoung Kim ◽  
Joonhyuk Kang ◽  
Yong Soo Cho

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