scholarly journals Eavesdropping and Jamming Selection Policy for Suspicious UAVs Based on Low Power Consumption over Fading Channels

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1126 ◽  
Author(s):  
Xiaoming Wang ◽  
Demin Li ◽  
Chang Guo ◽  
Xiaolu Zhang ◽  
Salil S. Kanhere ◽  
...  
Keyword(s):  
Power Consumption ◽  
Fading Channels ◽  
Unmanned Aerial Vehicle ◽  
Wireless Security ◽  
Low Power Consumption ◽  
Jamming Attacks ◽  
Weibull Fading ◽  
Selection Policy ◽  
Aerial Vehicle ◽  
Simulation Results

Traditional wireless security focuses on preventing unmanned aerial vehicle (UAV) communications from suspicious eavesdropping and/or jamming attacks. However, there is a growing need for governments to keep malicious UAV communications under legitimate surveillance. This paper first investigates a new surveillance paradigm for monitoring suspicious UAV communications via jamming suspicious UAVs. Due to the power consumption limitation, the choice of eavesdropping and jamming will reflect the performance of the UAVs communication. Therefore, the paper analyses the UAV’s eavesdropping and jamming models in different cases, and then proposes the model to optimize the data package in the constraints of lower power consumption, which can be solved by the proposed selection policy. The simulation results validate our proposed selection policy in terms of power consumption and eavesdropped packets. In different fading models, power consumption increases with time, regardless of distances, and our proposed policy performs better in Weibull fading channels in terms of eavesdropped packets.

scholarly journals PERANCANGAN AUTOPILOT LATERAL-DIREKSIONAL PESAWAT NIRAWAK LSU-05 (THE DESIGN OF THE LATERAL-DIRECTIONAL AUTOPILOT FOR THE LSU-05 UNMANNED AERIAL VEHICLE)

2018 ◽  
Vol 15 (2) ◽  
pp. 93 ◽  
Author(s):  
Muhammad Fajar ◽  
Ony Arifianto
Keyword(s):  
State Space ◽  
Linear Model ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Directional Motion ◽  
Aerial Vehicle ◽  
Simulation Results

The autopilot on the aircraft is developed based on the mode of motion of the aircraft i.e. longitudinal and lateral-directional motion. In this paper, an autopilot is designed in lateral-directional mode for LSU-05 aircraft. The autopilot is designed at a range of aircraft operating speeds of 15 m/s, 20 m/s, 25 m/s, and 30 m/s at 1000 m altitude. Designed autopilots are Roll Attitude Hold, Heading Hold and Waypoint Following. Autopilot is designed based on linear model in the form of state-space. The controller used is a Proportional-Integral-Derivative (PID) controller. Simulation results show the value of overshoot / undershoot does not exceed 5% and settling time is less than 30 second if given step command. Abstrak Autopilot pada pesawat dikembangkan berdasarkan pada modus gerak pesawat yaitu modus gerak longitudinal dan lateral-directional. Pada makalah ini, dirancang autopilot pada modus gerak lateral-directional untuk pesawat LSU-05. Autopilot dirancang pada range kecepatan operasi pesawat yaitu 15 m/dtk, 20 m/dtk, 25 m/dtk, dan 30 m/dtk dengan ketinggian 1000 m. Autopilot yang dirancang adalah Roll Attitude Hold, Heading Hold dan Waypoint Following. Autopilot dirancang berdasarkan model linier dalam bentuk state-space. Pengendali yang digunakan adalah pengendali Proportional-Integral-Derivative (PID). Hasil simulasi menunjukan nilai overshoot/undershoot tidak melebihi 5% dan settling time kurang dari 30 detik jika diberikan perintah step.

Elastic Formation Keeping Control of Unmanned Aerial Vehicle Adapting to Flight Speed

2013 ◽  
Vol 367 ◽  
pp. 411-416 ◽  
Author(s):  
Guang Yan Xu ◽  
Yi Bo Shi
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Relative Position ◽  
State Feedback ◽  
Feedback Controller ◽  
Flight Speed ◽  
Dynamic Equations ◽  
Aerial Vehicle ◽  
Distance Vector ◽  
Simulation Results ◽  
Formation Keeping

For an Unmanned Aerial Vehicle (UAV) formation in leader-follower mode, considering the relative position relationship between neighbor vehicles in the formation, an elastic distance vector is proposed. The dynamic equations of a flight speed adaptive UAV formation are established using the elastic distance vector we proposed. The state feedback controller is designed. Simulation results show that the controller can be used to control the follower vehicles to follow the leader vehicle maneuvering effectively and keep the desired formation well, most importantly, the relative distance between neighbor vehicles in the formation is adapted to the changes of flight speed.

Swarming Algorithm for Unmanned Aerial Vehicle (UAV) Quadrotors – Swarm Behavior for Aggregation, Foraging, Formation, and Tracking –

2014 ◽  
Vol 18 (5) ◽  
pp. 745-751 ◽  
Author(s):  
Argel A. Bandala ◽  
◽  
Elmer P. Dadios ◽  
Ryan Rhay P. Vicerra ◽  
Laurence A. Gan Lim
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Computer Simulations ◽  
Group Performance ◽  
Robotic System ◽  
Robot Swarms ◽  
Average Accuracy ◽  
Swarm Behavior ◽  
Aerial Vehicle ◽  
Simulation Results ◽  
Robotic Agent

This paper presents the fusion of swarm behavior in multi robotic system specifically the quadrotors unmanned aerial vehicle (QUAV) operations. This study directed on using robot swarms because of its key feature of decentralized processing amongst its member. This characteristic leads to advantages of robot operations because an individual robot failure will not affect the group performance. The algorithm emulating the animal or insect swarm behaviors is presented in this paper and implemented into an artificial robotic agent (QUAV) in computer simulations. The simulation results concluded that for increasing number of QUAV the aggregation accuracy increases with an accuracy of 90.62%. The experiment for foraging revealed that the number of QUAV does not affect the accuracy of the swarm instead the iterations needed are greatly improved with an average of 160.53 iterations from 50 to 500 QUAV. For swarm tracking, the average accuracy is 89.23%. The accuracy of the swarm formation is 84.65%. These results clearly defined that the swarm system is accurate enough to perform the tasks and robust in any QUAV number.

Dynamic Modeling for a Miniature Six-Rotor Unmanned Aerial Vehicle

2013 ◽  
Vol 321-324 ◽  
pp. 819-823 ◽  
Author(s):  
Qi Dong Ma ◽  
Zhen Guo Sun ◽  
Jing Ran Wu ◽  
Wen Zeng Zhang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Driving Force ◽  
Pid Controller ◽  
Control Algorithm ◽  
Driving Forces ◽  
Euler Angles ◽  
Unstable System ◽  
Nonlinear Dynamic Model ◽  
Aerial Vehicle ◽  
Simulation Results

A nonlinear dynamic model of a miniature Six-Rotor is presented. A 4 channels PID controller is designed to operate the under actuated and dynamically unstable system with 6 inputs. Driving forces of 6 rotors are divided into four components such as throttle, roll, pitch and yaw. The control algorithm is simulated with Design Optimization Toolbox in Matlab. After observing the corresponding responses of Euler angles, the altitude and the driving force for each motor, the simulation results show good performance.

A 3-D Geometry-Based Stochastic Model for Unmanned Aerial Vehicle MIMO Ricean Fading Channels

2020 ◽  
Vol 7 (9) ◽  
pp. 8674-8687
Author(s):  
Xiang Cheng ◽  
Yiran Li ◽  
Cheng-Xiang Wang ◽  
Xuefeng Yin ◽  
David W. Matolak
Keyword(s):  
Stochastic Model ◽  
Fading Channels ◽  
Unmanned Aerial Vehicle ◽  
Ricean Fading ◽  
Aerial Vehicle

scholarly journals Node Deployment in Farmland Wireless Sensor Networks based on Renewable Energy

2016 ◽  
Vol 12 (10) ◽  
pp. 62
Author(s):  
Jianwei Wu ◽  
Yisheng Miao
Keyword(s):  
Wireless Sensor Networks ◽  
Power Consumption ◽  
Large Scale ◽  
Hot Spot ◽  
Wireless Sensor ◽  
Low Power Consumption ◽  
Network Coverage ◽  
Font Size ◽  
Deployment Strategy ◽  
Simulation Results

<p><span style="font-size: small;"><span style="font-family: Times New Roman;">Wireless sensor network (WSN) plays an important role in the large scale farmland environmental monitoring. The complex farmland environment has a great impact on the WSN performance. Extremely low power consumption of WSN is required because of the long monitoring period and limited energy. In the considering of network coverage, connectivity, organization and power consumption, this paper proposes a new deployment strategy in the consideration of solar power nodes. A mixed deployment method combining with structure and random filling deployment is used. The hot-spot nodes in the network are replaced by solar nodes in order to get a longer lifetime. The simulation results show that the new method has a better performance than the traditional algorithms.</span></span></p>

Takeoff Analysis and Simulation of a Small Scaled UAV with a Rocket Booster

2011 ◽  
Vol 267 ◽  
pp. 674-682 ◽  
Author(s):  
Bo Liu ◽  
Zhou Fang ◽  
Ping Li ◽  
Chuan Chuan Hao
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Unmanned Aerial Vehicle ◽  
Nonlinear Dynamic ◽  
Total Mass ◽  
Nonlinear Dynamic Model ◽  
Centre Of Gravity ◽  
Acceptable Range ◽  
Aerial Vehicle ◽  
Simulation Results

This paper analyses the takeoff process of a small scaled UAV (unmanned aerial vehicle) with a single rocket booster. Because the thrust provided by the rocket booster is 10 times as large as the thrust provided by the engines, the effects caused by the boosting rocket on total mass, compound centre of gravity and inertia can not be neglected and are all considered. The inertia of the boosting rocket is calculated by the means of finite element method. Based on the analysis, a nonlinear dynamic model of the UAV is built. Several simulations with different takeoff parameters are conducted to test the takeoff performance. By analyzing simulation results, the acceptable range of boosting angle is investigated.

scholarly journals Robust Edge Computing in UAV Systems via Scalable Computing and Cooperative Computing

2021 ◽  
Author(s):  
Zhi Liu ◽  
Cheng Zhan ◽  
Ying Cui ◽  
Celimuge Wu ◽  
Han Hu
Keyword(s):  
Video Streaming ◽  
Unmanned Aerial Vehicle ◽  
Edge Computing ◽  
Future Research ◽  
Mobile Edge Computing ◽  
Computing Power ◽  
Aerial Vehicle ◽  
Cooperative Computing ◽  
Computing Performance ◽  
Simulation Results

<div>Unmanned aerial vehicle (UAV) systems are of increasing interest to academia and industry due to their mobility, flexibility and maneuverability, and are an effective alternative to various uses such as surveillance and mobile edge computing (MEC). However, due to their limited computational and communications resources, it is difficult to serve all computation tasks simultaneously. This article tackles this problem by first proposing a scalable aerial computing solution, which is applicable for computation tasks of multiple quality levels, corresponding to different computation workloads and computation results of distinct performances. It opens up the possibility to maximally improve the overall computing performance with limited computational and communications resources. To meet the demands for timely video analysis that exceed the computing power of a UAV, we propose an aerial video streaming enabled cooperative computing solution namely, UAVideo, which streams videos from a UAV to ground servers. As a complement to scalable aerial computing, UAVideo minimizes the video streaming time under the constraints on UAV trajectory, video features, and communications resources. Simulation results reveal the substantial advantages of the proposed solutions. Besides, we highlight relevant directions for future research.</div>

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