scholarly journals Target Cooperative Location Method of Multi-UAV Based on Pseudo Range Measurement

2019 ◽  
Vol 37 (2) ◽  
pp. 266-272 ◽  
Author(s):  
Yaohong Qu ◽  
Feng Zhang ◽  
Renneng Gu ◽  
Dongli Yuan
Keyword(s):  
Nonlinear Equation ◽  
Unmanned Aerial Vehicles ◽  
Position Information ◽  
Distance Information ◽  
Location Accuracy ◽  
Location Method ◽  
Range Measurement ◽  
Location Errors ◽  
Aerial Vehicles ◽  
Multi Uav

Based on the locations of several unmanned aerial vehicles (UAVs) and the pseudo ranges to a target, a target cooperative location method is proposed in this paper. The nonlinear equation about real pseudo distance information is transformed to another equation by using Tayloy formula. By solving the above equation, position information of the target can be obtained. Meanwhile, the certain equation's variables are the measured results of pseudo distances, location errors of UAVs and distance-measuring errors of range sensors. Besides, an online enumeration method is applied to search for the best formation, whose objective is to enhance the location accuracy, and the mentioned formation is mapped to the minimal GDOP. The simulations verify the validity and adaptability of the proposed method.

scholarly journals Autonomous Integrity Monitoring for Relative Navigation of Multiple Unmanned Aerial Vehicles

2021 ◽  
Vol 13 (8) ◽  
pp. 1483
Author(s):  
Yuan Sun
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Real Data ◽  
Wide Band ◽  
Relative Navigation ◽  
Monitoring Method ◽  
Integrity Monitoring ◽  
Position Information ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Multi Uav

Accurate and reliable relative navigation is the prerequisite to guarantee the effectiveness and safety of various multiple Unmanned Aerial Vehicles (UAVs) cooperation tasks, when absolute position information is unavailable or inaccurate. Among the UAV navigation techniques, Global Navigation Satellite System (GNSS) is widely used due to its worldwide coverage and simplicity in relative navigation. However, the observations of GNSS are vulnerable to different kinds of faults arising from transmission degradation, ionospheric scintillations, multipath, spoofing, and many other factors. In an effort to improve the reliability of multi-UAV relative navigation, an autonomous integrity monitoring method is proposed with a fusion of double differenced GNSS pseudoranges and Ultra Wide Band (UWB) ranging units. Specifically, the proposed method is designed to detect and exclude the fault observations effectively through a consistency check algorithm in the relative positioning system of the UAVs. Additionally, the protection level for multi-UAV relative navigation is estimated to evaluate whether the performance meets the formation flight and collision avoidance requirements. Simulated experiments derived from the real data are designed to verify the effectiveness of the proposed method in autonomous integrity monitoring for multi-UAV relative navigation.

scholarly journals Distributed Cooperative Avoidance Control for Multi-Unmanned Aerial Vehicles

Actuators ◽  
2018 ◽  
Vol 8 (1) ◽  
pp. 1 ◽  
Author(s):  
Sunan Huang ◽  
Rodney Swee Huat Teo ◽  
Wenqi Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Case Studies ◽  
Collision Avoidance ◽  
Hardware In The Loop ◽  
Crucial Issue ◽  
Communication Failure ◽  
Aerial Vehicles ◽  
Avoidance Control ◽  
Velocity Obstacle ◽  
Multi Uav

It is well-known that collision-free control is a crucial issue in the path planning of unmanned aerial vehicles (UAVs). In this paper, we explore the collision avoidance scheme in a multi-UAV system. The research is based on the concept of multi-UAV cooperation combined with information fusion. Utilizing the fused information, the velocity obstacle method is adopted to design a decentralized collision avoidance algorithm. Four case studies are presented for the demonstration of the effectiveness of the proposed method. The first two case studies are to verify if UAVs can avoid a static circular or polygonal shape obstacle. The third case is to verify if a UAV can handle a temporary communication failure. The fourth case is to verify if UAVs can avoid other moving UAVs and static obstacles. Finally, hardware-in-the-loop test is given to further illustrate the effectiveness of the proposed method.

scholarly journals A New Password- and Position-Based Authenticated Key Exchange

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jia Fan ◽  
Lanfei Qiao ◽  
Yunfei Cao ◽  
Shanglin Liu ◽  
Wenke Zhang ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Key Exchange ◽  
Authenticated Key Exchange ◽  
Key Exchange Protocol ◽  
Position Information ◽  
Popular Method ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Secure Authentication ◽  
The Military

Password-based authenticated key exchange is a popular method for secure authentication and key exchange. With the wide application of unmanned aerial vehicles, position information has also become an important factor in authentication. In this paper, we present a new key exchange protocol, which firstly realizes dual authentication for both password and position, and we propose two applicable scenarios for the PPAKE mechanism: one is unmanned aerial vehicle authentication, and the other one is authentication in the military base. By adding position authentication, the reliability of authentication has improved, and the difficulty of adversarial attacks also increases. Any arbitrary adversary who can listen, tamper, and send messages can only perform an online attack for password guessing at a specified position. Finally, we provide security proofs under the defined model.

Forest Firefighting Monitoring System Based on UAV Team and Remote Sensing

2019 ◽  
pp. 220-241
Author(s):  
Maryna Zharikova ◽  
Vladimir Sherstjuk
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Unmanned Aerial Vehicles ◽  
Monitoring System ◽  
Fire Response ◽  
Ground Support ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Fire Spreading ◽  
Multi Uav

In this chapter, the authors propose an approach to using a heterogeneous team of unmanned aerial vehicles and remote sensing techniques to perform tactical forest firefighting operations. The authors present the three-level architecture of the multi-UAV-based forest firefighting monitoring system; features of patrolling, confirming, and monitoring missions; as well as functions of UAV in such missions. The authors consider an infrastructure for the UAV ground support and equipment used for the UAVs control. The method of the data integration into a fire-spreading model in a real-time DSS for the forest fire response is proposed. The proposed approach has been tested with the multi-UAV team that included three drones for the patrol missions, one helicopter for the confirmation mission, and one octocopter for the monitoring mission. The performance of such multi-UAV team has been studied in the laboratory conditions. The result of the experiment has shown that the proposed approach provides required credibility and efficiency of fire prediction and response.

Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

2020 ◽  
Vol 08 (04) ◽  
pp. 269-277
Author(s):  
Patricio Moreno ◽  
Santiago Esteva ◽  
Ignacio Mas ◽  
Juan I. Giribet
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
Field Experiments ◽  
Aerial Vehicles ◽  
Simulated Environment ◽  
Aerial Vehicle ◽  
Space Formulation ◽  
Trajectory Following ◽  
And Control ◽  
Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

scholarly journals Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoxuan Hu ◽  
Jing Cheng ◽  
He Luo
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Task Assignment ◽  
Uncertain Information ◽  
Simulation Experiments ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Severe Uncertainty ◽  
Task Assignment Problem ◽  
Multi Uav ◽  
Assignment Approach

This paper considers a task assignment problem for multiple unmanned aerial vehicles (UAVs). The UAVs are set to perform attack tasks on a collection of ground targets in a severe uncertain environment. The UAVs have different attack capabilities and are located at different positions. Each UAV should be assigned an attack task before the mission starts. Due to uncertain information, many criteria values essential to task assignment were random or fuzzy, and the weights of criteria were not precisely known. In this study, a novel task assignment approach based on stochastic Multicriteria acceptability analysis (SMAA) method was proposed to address this problem. The uncertainties in the criteria were analyzed, and a task assignment procedure was designed. The results of simulation experiments show that the proposed approach is useful for finding a satisfactory assignment under severe uncertain circumstances.

scholarly journals Mission Planning for Unmanned Aerial Vehicles Based on Voronoi Diagram-Tabu Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Wei Tan ◽  
Yong-jiang Hu ◽  
Yue-fei Zhao ◽  
Wen-guang Li ◽  
Xiao-meng Zhang ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Unmanned Aerial Vehicles ◽  
Voronoi Diagram ◽  
Pso Algorithm ◽  
Mission Planning ◽  
Cooperative System ◽  
Aerial Vehicles ◽  
Rendezvous Problem ◽  
Aerial Vehicle ◽  
Multi Uav

Unmanned aerial vehicles (UAVs) are increasingly used in different military missions. In this paper, we focus on the autonomous mission allocation and planning abilities for the UAV systems. Such abilities enable adaptation to more complex and dynamic mission environments. We first examine the mission planning of a single unmanned aerial vehicle. Based on that, we then investigate the multi-UAV cooperative system under the mission background of cooperative target destruction and show that it is a many-to-one rendezvous problem. A heterogeneous UAV cooperative mission planning model is then proposed where the mission background is generated based on the Voronoi diagram. We then adopt the tabu genetic algorithm (TGA) to obtain multi-UAV mission planning. The simulation results show that the single-UAV and multi-UAV mission planning can be effectively realized by the Voronoi diagram-TGA (V-TGA). It is also shown that the proposed algorithm improves the performance by 3% in comparison with the Voronoi diagram-particle swarm optimization (V-PSO) algorithm.

Three-dimensional image coordinate-based missing region of interest area detection and damage localization for bridge visual inspection using unmanned aerial vehicles

2020 ◽  
pp. 147592172091867
Author(s):  
Sungsik Yoon ◽  
Gi-Hun Gwon ◽  
Jin-Hwan Lee ◽  
Hyung-Jo Jung
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Visual Inspection ◽  
Experimental Validation ◽  
Three Dimensional ◽  
Region Of Interest ◽  
Field Of View ◽  
Damage Localization ◽  
Distance Information ◽  
Dimensional Image ◽  
Aerial Vehicles

In this study, the three-phase missing region of interest area detection and damage localization methodology based on three-dimensional image coordinates was proposed. In Phase 1, the coordinate transformation is performed by the position and attitude information of the unmanned aerial vehicles and camera, and the coordinates of the center point of each acquired image are obtained with the distance information between the camera and the target surface. For Phase 2, the size of the field of view of every acquired image is calculated using the focal length and working distance of the camera. Finally, in Phase 3, the missing part of the region of interest area can be identified and any damage detected at the individual image level can also be localized on the whole inspection region using information about the sizes of the field of view in all images calculated in the previous phase. In order to demonstrate the proposed methodology, experimental validation was performed on the actual bridge pier and deck as well as the lab-scale concrete shear wall. In the tests, the missing area detection and damage localization results were compared with image stitching and human visual inspection results, respectively. Experimental validation results have shown that the proposed methodology identifies missing areas and damage locations within reasonable accuracy of 10 cm.

scholarly journals Cooperative Attack-Defense Decision-Making of Multi-UAV Using Satisficing Decision-Enhanced Wolf Pack Search Algorithm

2021 ◽  
Author(s):  
Tongle Zhou ◽  
Mou Chen ◽  
Yuhui Wang ◽  
Ronggang Zhu ◽  
Chenguang Yang
Keyword(s):  
Decision Making ◽  
Unmanned Aerial Vehicles ◽  
Decision Problem ◽  
Search Algorithm ◽  
Optimal Solution ◽  
Target Information ◽  
Aerial Vehicles ◽  
Air Combat ◽  
Simulation Results ◽  
Multi Uav

Abstract Unmanned Aerial Vehicles (UAVs) have shown their superiority for applications in complicated military missions. A cooperative attack-defense decision-making method based on satisficing decision-enhanced wolf pack search (SDEWPS) algorithm is developed for multi-UAV air combat in this paper. Firstly, the multi-UAV air combat mathematical model is provided and the attack-defense decision-making constraints are defined. Besides the traditional air combat situation, the capability of UAVs and target information including target type and target intention are all considered in this paper to establish the air combat superiority function. Then, the wolf pack search (WPS) algorithm is used to solve the attack decision problem. In order to improve efficiency, the satisficing decision theory is employed to enhance the WPS to obtain the satisficing solution rather than optimal solution. The simulation results show that the developed method can realize the cooperative attack decision-making.

Model decomposition-based optimal formation control for multiple unmanned aerial vehicles

2021 ◽  
pp. 014233122110430
Author(s):  
Khan Muhammad Shehzad ◽  
Hao Su ◽  
Gong-You Tang ◽  
Bao-Lin Zhang
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Control ◽  
Controller Design ◽  
Feedforward Control ◽  
Position Information ◽  
Model Decomposition ◽  
Aerial Vehicles ◽  
Control Framework ◽  
Multiple Unmanned Aerial Vehicles ◽  
The Stability

This paper deals with the optimal formation control problem based on model decomposition for multiple unmanned aerial vehicles (UAVs). The main contribution of this paper is to integrate the formation control and the trajectory tracking into one unified feedforward control and feedback control framework in an optimal mode. We first establish the dynamic model of the leader-follower UAV formation system, and the communication network topology which only depends on the position information given by the leader. Second, to reduce the complexity of the model, each follower is decomposed into three isolated subsystems. Third, a step-by-step formation controller design scheme decomposed into feedforward control and optimal control of formation control is proposed. Finally, the proposed scheme has been extensively simulated and the results demonstrate the stability and the optimality.

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