Group Of UAVs Research Articles

User‐Centric UAV Group Power Allocation Algorithm

User‐centric unmanned aerial vehicle group (UUAVG) organizes a dynamic user‐centric access point group for each user, which can improve user service quality and throughput. However, in UUAVG, unmanned aerial vehicle user equipment (UUE) and device‐to‐device user equipment (DUE) using the same frequency will cause co‐frequency interference and reduce system performance. In response to this problem, a power allocation algorithm of the two‐level Stackelbreg game (PAOTLSG) is proposed. The algorithm builds a two‐level Stackelberg game model based on UUE and DUE and uses power control coefficients and other parameters to control UAV adjust with the transmit power of DUE to achieve dynamic balance. The optimal transmit power of UAV and DUE is theoretically deduced to achieve the game Nash equilibrium and theoretically prove the existence and uniqueness of the Nash equilibrium solution. The simulation results show that compared with the pricing‐based Stackelbreg game (PSG) algorithm, the PAOTLSG algorithm can effectively increase the throughput by 4.65%.

Performance Analysis of Group Selection in UAV Networks with Backhaul‐Aware Biasing

The limited wireless backhaul capacity has become the major bottleneck for UAV communications, while in existing researches of UAV networks, the relation between cell selection and backhaul capacity has not been modeled. This paper proposes cell group selection with backhaul‐aware biasing for UAV networks and analyzes system performance by deriving the rate outage probability via stochastic geometry, where the user’s maximum data rate is constrained by backhaul capacity. Specifically, cell group selection is no longer distance‐based and considered with backhaul capacity bias factor, where UAVs with higher backhaul capacity will have a larger bias factor to match the backhaul variance. In addition, the dynamic UAV group is organized with the N largest bias reference signal receiving power (BRSRP), where users can utilize the diversity gain by adjusting serving UAV dynamically as the channel conditions change. Analytical results show that the outage probability is decreased by 58% when cell group size N = 3 and UAV optimal density λu = 600/km2 when UAV height h = 150 m.

Управление группой БЛА при неопределенных запаздываниях в каналах связи

The UAV groups and other unmanned robots are more and more widely used to solve production and special problems in view of their bigger efficiency in comparison with single robots. The efficiency of a group in many respects is defined by the opportunities of the communications means between members of the group and its leader, which influences the efficiency of the decisions made. The control of the UAV group is often exercised by a multivariable control system whose algorithms are implemented by a computer complex of the group UAV leader. The problem here is that in individual channels of information exchanges between the UAV-leader and other UAVs of the group there is a time delay. Any space distributions of the UAV in the neighborhood of the leader cause significantly different, uncertain delays in channels of its contact with the UAV group that can lead to a loss of control stability. It is proposed to apply a multivariable, robust to delay control system to overcome this difficulty. The design of this system is carried out on the basis of the matrix decoupling control and the method of an analytical design of systems with control on output and impact (ADSCOI) taking into account conditions of feasibility of controls on digital computing elements. Analytical expressions including the solution to the linear system algebraic equations and the creation procedure of the digital control algorithms are found in the article. This control provides robustness of the system to delays in communication channels. The efficiency of the proposed approach is illustrated by a numerical design example of the multivariable group control system of the UAV. The results obtained can be applied to create digital control systems by both single input-single-output and multi-input-multi-output objects with an uncertain delay in agricultural, food, power, machine-building and other industries.

Model of Control in a UAV Group for Hidden Transmitters Detection on the Basis of Local Self-Organization

Model of Control in a UAV Group for Hidden Transmitters Detection on the Basis of Local Self-Organization

Multiaccess Edge Computing Empowered Flying Ad Hoc Networks with Secure Deployment Using Identity-Based Generalized Signcryption

A group of small UAVs can synergize to form a flying ad hoc network (FANET). The small UAVs are, typically, prone to security lapses because of limited onboard power, restricted computing ability, insufficient bandwidth, etc. Such limitations hinder the applicability of standard cryptographic techniques. Thus, assuring confidentiality and authentication on part of small UAV remains a far-fetched goal. We aim to address such an issue by proposing an identity-based generalized signcryption scheme. The lightweight security scheme employs multiaccess edge computing (MEC) whereby the primary UAV, as a MEC node, provides offloading to the computationally fragile member UAVs. The scheme is based on the concept of the hyperelliptic curve (HEC), which is characterized by a smaller key size and is, therefore, suitable for small UAVs. The scheme is robust since it offers confidentiality and authentication simultaneously as well as singly. Formal as well as informal security analyses and the validation results, using the Automated Validation for Internet Security Validation and Application (AVISPA) tool, second such notion. Comparative analysis with the existing schemes further authenticates the sturdiness of the proposed scheme. As a case study, the scheme is applied for monitoring crops in an agricultural field. It has been found out that the scheme promises higher security and incurs lower computational and communication costs.

Adaptive and Extensible Energy Supply Mechanism for UAVs-Aided Wireless-Powered Internet of Things

This article studies multiple unmanned aerial vehicles (multi-UAVs)-enabled wireless-powered Internet of Things (IoT), where a group of UAVs is dispatched as mobile power sources to charge a set of ground IoT devices. Different from the conventional radio-frequency (RF) wireless power transfer (WPT) systems, magnetic resonance-coupled (MRC) WPT systems can guarantee high power transfer efficiency without the complete alignment, which is remarkable. In this article, we extend the charging range by the wired connection between the energy receiving systems and IoT devices. Due to the restriction of carriable energy on the UAVs, designing the shortest possible trajectory for each UAV is necessary. We formulate it as a multidepots multi-UAVs trajectory optimization problem, jointly with constraints of the UAV’s energy capacity and the area of the target region, to maximize the resource utilization of UAVs. To tackle this nonconvex problem, we decompose it into two subproblems, i.e., hovering locations selection and multi-UAVs trajectory optimization. For the first subproblem, we propose two approximation algorithms to obtain the near-optimal solution in the sparse networks. Then, we adopt a heuristic algorithm, a memetic algorithm-based variable neighborhood search (MAVNS), to achieve the quasioptimal trajectory rapidly. Finally, extensive numerical results are provided to evaluate the performance of the proposed algorithms. New insights are investigated on the estimation of feasibility that whether the given UAVs with energy capacity constraint can fully charge ground IoT devices within open areas.

The Research of Slot Adaptive 4D Network Clustering Algorithm Based on UAV Autonomous Formation and Reconfiguration

Being independent of any fixed equipment, Ad Hoc wireless sensor networks, a kind of acentric and self-organized wireless network, possesses some features such as easiness of deployment, strong invulnerability and flexibility of networking, which leads to a promising application prospect in terms of UAV military and civilian use. This paper proposes a new slot adaptive 4D network clustering algorithm based on UAV autonomous formation and reconfiguration to solve the problem of UAV Ad Hoc network such as networking confusion, poor network reconstruction performance, huge energy consumption and other issues. The algorithm can optimize the topology of UAVs network. We build the network topology and generate clustering network by the slot adaptive 4D network clustering algorithm in Matlab. According to the real combat of UAV, four states are simulated and analyzed. The simulation results validate the feasibility of the slot adaptive 4D network clustering algorithm. The clustering structure generated by the slot adaptive 4D network clustering algorithm is robust and the algorithm is suitable for the UAV group operation.

Research on guidance method of cooperative tracking ground multi-target using UAV group

Multi-UAV (unmanned aerial vehicle) cooperative tracking target is one of the standard exercises for unmanned aircraft systems, it is important to track multiple targets in actual missions due to the clustering of military missions. It is of great research interest and more difficult to use fewer multi-UAV to track more targets effectively, the aim of which is to be more efficient in tracking, and high precision positioning. This paper explores the key issues in the complex environment of UAV community cooperative multi-target monitoring. The architecture of the UAV group cooperative the multi-target tracking system is built in a complex environment firstly. Then a proposal was made for a dynamic grouping algorithm for multi-target UAV group tracking in an occlusion region, an adaptive multi-model unscented Kalman particle filter fusion algorithm, and a fast guidance method for cooperative target tracking in a restricted environment. The feasibility of the proposed method is validated by simulation and flight test evaluations. Finally, there is a prospect for the next course of research in this field.

A distributed flocking control strategy for UAV groups

To ensure the information security of UAV groups, maximize the detection range of the UAV group and minimize the communication range, this paper improves Olfati–Saber’s flocking algorithm using virtual leader and integrates the multiple UAVs with real environment. The improved swarm control algorithm can help to make all agents accurately track the speed of virtual leaders. Then, we introduce the conception of virtual communication circle to control the communication power of each UAV, and the moving function of the target position is improved to meet the limited conditions of given communication distance, to ensure the non-collision and stable communication of the UAV during the moving process. All UAVs in the group system will keep converging, avoiding collision and the speed is the same as that of the virtual pilot. Therefore, multiple UAVs can track the virtual pilot for cluster flight and a distributed cooperative control strategy can be acquired. The simulation results show that the strategy proposed in this paper makes a better communication performance among UAVs in real time, and the UAV groups achieve the information more timely, which is proved to be an effective way to ensure the security communication among multiple UAVs.

某型无人机群的监视覆盖任务航路规划

某型无人机群的监视覆盖任务航路规划

基于改进人工势场方法的无人机群侦察覆盖航路规划算法研究

基于改进人工势场方法的无人机群侦察覆盖航路规划算法研究

Experimental evaluation of efficiency of algorithms for direction finding of unmanned aerial vehicles by acoustic radiation

The results of an experimental evaluation of Bartlett, Capon algorithms and cross-correlation function method effectiveness for direction finding of unmanned aerial vehicles are presented. Full-scale studies were carried out using a harmonic signal and acoustic radiation of a prototype of a propeller-driven UAV group indoors and in open space, as well as in real-world conditions of flight modes and UAV hovering. The acoustic emission spectrum of the electric propeller-motor group of modern UAVs includes narrow-band tonal and broadband noise-like components with predominant propeller radiation. The use of algorithms for determining the direction of arrival of acoustic radiation from the spatial spectrum by the methods of Bartlett and Capon involves the use of narrow-band signals. It is shown that to work with UAV acoustic radiation, the MB, MK, and cross-correlation function algorithms require some adaptation (including the use of high-pass filters). The Capon method has a significantly higher resolution than the classic Bartlett method, and a lower level of side lobes. The presence of significant reflections from local objects leads to the appearance of abnormal bearing estimates for the acoustic signal source of the propeller-driven UAV group. The results of determining the bearing of the source of acoustic radiation in a wide frequency band in open space show good agreement with the specified values of the bearing when applying the method of mutual correlation function. To increase the efficiency of the mutual correlation function algorithm when processing UAV acoustic signals, it is necessary to reduce the influence of low-frequency interference caused by anthropogenic and natural acoustic noise.

GeoUAVs: A new geocast routing protocol for fleet of UAVs

Routing in cooperative UAVs networks is a challenging task due to mobility of nodes, dynamically changing topology and three-dimensional (3D) movement. In this work, we study the fleet routing problem in FANET, which aims at delivering data to a specific group of mobile drones identified by their geographical location. Although many fleet routing protocols have been proposed, only partial inherent constraints of FANET (such as mobility, 3D movement and reliability) are taken into account. Therefore, we propose a new geocast routing protocol namely Geocast routing protocol for fleet of UAVs (GeoUAVs). This protocol aims at delivering information to a specific group of mobile UAVs identified by their geographical location. It takes into account the mobility of nodes, dynamic changing topology with 3D movement, and reliability. Simulations conducted in NS-3 simulator demonstrate that our proposal GeoUAVs outperforms AntHocNet and BeeAdHoc protocols by reducing the average delay by more than to 61% and increasing both the packet delivery ratio and throughput.

A multi-UAV clustering strategy for reducing insecure communication range

Multi-unmanned aerial vehicle (UAV) flight formations can be deployed to monitor large areas. Individual UAVs communicate and exchange information while formation flying. but, such communication presents a security risk. The area between the UAV group range and the group communication range is called the insecurity range and in this region multi-UAV communication can cause serious information leakage. To resolve this problem, this paper considers two aspects, namely, cooperative control and secure communication. To implement cooperative control, a clustering algorithm is presented to accelerate the speed at which the multi-UAV formation converges. By setting the flight control factor to accelerate the convergence of multi-UAV, the UAV group forms a flock. To facilitate secure communication, the hierarchical virtual communication ring (HVCR) strategy is deployed to reduce the boundary of group communication and minimize the insecure range. The effectiveness of the clustering algorithm and HVCR strategy is demonstrated via theoretical analysis and experiments. In the case of 50 and 100 nodes, the results show that the clustering algorithm can facilitate multi-UAV group flocks. In the case of 25, 30, 35 and 40 nodes, the HVCR strategy can reduce the relative size of the insecure range to 65.33%, 62.95%, 61.50% and 60.55%, respectively.

Applying partial domination in organizing the control of the heterogeneous robot group

The article discusses the formulation of the problem of multicriteria design of a robotic system consisting of a group of robots, with the aim of achieving specified targets. A new approach to organizing the control of such robotic systems based on the partial dominance of decisions over target indicators is proposed. Illustrative examples of the application of the approach for UAV groups are given.

Steady flight of miniature fixed-wing unmanned aerial vehicle flocking by using biological algorithm

This paper focuses on solving cohesive flocking problem from the biological point of view. Twelve variables are adopted to draw the kinematic characteristics of the fixed-wing UAV. A weighted and undirected graph is applied to describe the time-variant and distance-related interaction relationship among the UAVs. Based on the proposed model and the communication mechanism, a distributed cooperation approach is designed to force groups of miniature fixed-wing UAVs to be capable of collaboratively accomplishing such predefined task like a flock of birds. During the evolutionary process, three constraint conditions should be considered. The first one is that each UAV flies under small roll angle and small pitch angle. Second, one forward speed is necessary for the flight of each fixed-wing UAV. The last constraint condition is that the shorter the adjustment time, the better within the error margin of steady-state value. Three constraint conditions are skilfully taken as evaluation criteria to determine the communication network's coupling strength. Numerical simulations are provided to validate the feasibility of the proposed approach.

Interference-Aware Cooperative Anti-Jamming Distributed Channel Selection in UAV Communication Networks

This paper investigates the cooperative anti-jamming distributed channel selection problem in UAV communication networks. Considering the existence of malicious jamming and co-channel interference, we design an interference-aware cooperative anti-jamming scheme for the purpose of maximizing users’ utilities. Moreover, the channel switching cost and cooperation cost are introduced, which have a great impact on users’ utilities. Users in the UAV group sense the co-channel interference signal energy to judge whether they are influenced by co-channel interference. When the received co-channel interference signal energy is lower than the co-channel interference threshold, users conduct channel selection strategies independently. Otherwise, users cooperate with each other and take joint actions with a cooperative anti-jamming pattern under the impact of co-channel interference. Aiming at the independent anti-jamming channel selection problem under no co-channel interference, a Markov decision process framework is introduced, whereas for the cooperative anti-jamming channel selection case under the influence of co-channel mutual interference, a Markov game framework is employed. Furthermore, motivated by Q-learning with a “cooperation-decision-feedback-adjustment” idea, we design an interference-aware cooperative anti-jamming distributed channel selection algorithm (ICADCSA) to obtain the optimal anti-jamming channel strategies for users in a distributed way. In addition, a discussion on the quick decision for UAVs is conducted. Finally, simulation results show that the proposed algorithm converges to a stable solution with which the UAV group can avoid malicious jamming, as well as co-channel interference effectively and can realize a quick decision in high mobility UAV communication networks.

Dynamic Routing Method over Hybrid SDN for Flying Ad Hoc Networks

Due to the high mobility and dynamic topology of the FANET network, maintaining communication links between UAVs is a challenging task. The topology of these networks is more dynamic than traditional mobile networks, which raises challenges for the routing protocol. The existing routing protocols for these networks partly fail to detect network topology changes. Few methods have recently been proposed to overcome this problem due to the rapid changes of network topology. We try to solve this problem by designing a new dynamic routing method for a group of UAVs using Hybrid SDN technology (SDN and a distributed routing protocol) with a highly dynamic topology. Comparison of the proposed method performance and two other algorithms is simulated. The simulation results show that the proposed method has better results than traditional algorithms in the package delivery ratio, average end to end delay, packet loss, throughput and normalized routing Load.

UAVs Group Control Based on the Relative State Space Method

UAVs Group Control Based on the Relative State Space Method

Coordinated Standoff Target Tracking Guidance Method for UAVs

We need a coordinated control method to continuously track a moving target using a group of UAVs. In this paper, we study the predicted reference point guidance method, where the target is considered to move with a constant velocity in a very short time window and the trajectories of the UAVs are designed as several tiny arcs around the target. The control law of the UAV is divided into roll angle control and velocity control. Simulations are used to verify that the proposed control laws have smaller standoff distances and phase angle control errors than the Lyapunov vector field guidance and model-based predictive control, and the wind is considered in the simulation, too. Therefore, we show that our proposed method has higher steady state accuracy among existing techniques.