Management Of Unmanned Aerial Vehicles Research Articles

Distributed Detect-and-Avoid for Multiple Unmanned Aerial Vehicles in National Air Space

Small unmanned aerial vehicles (UAVs) have the potential to revolutionize various applications in civilian domain such as disaster management, search and rescue operations, law enforcement, precision agriculture, and package delivery. As the number of such UAVs rise, a robust and reliable traffic management is needed for their integration in national airspace system (NAS) to enable real-time, reliable, and safe operation. Management of UAVs traffic in NAS becomes quite challenging due to issues such as real-time path planning of large number of UAVs, communication delays, operational uncertainties, failures, and noncooperating agents. In this work, we present a novel UAV traffic management (UTM) architecture that enables the integration of such UAVs in NAS. A combined A*–mixed integer linear programming (MILP)-based solution is presented for initial path planning of multiple UAVs with individual mission requirements and dynamic constraints. We also present a distributed detect-and-avoid (DAA) algorithm based on the concept of resource allocation using a market-based approach. The results demonstrate the scalability, optimality, and ability of the proposed approach to provide feasible solutions that are versatile in dynamic environments.

Aerial Control System for Spectrum Efficiency in UAV-to-Cellular Communications

The next generation of mobile systems, 5G, will be the communication standard that accommodates the proliferation of the Internet of Things (IoT). Unmanned aerial vehicles (UAVs) are envisioned to support many applications in providing 5G connectivity to the IoT, by extending highspeed connectivity from the sky to objects on the ground, or even by carrying onboard some IoT devices. However, given their critical nature, the management of UAVs induces high exchange of control messages with the ground control station, resulting in the crowded spectrum used by cellular networks. The authors raise the problem of degrading the network spectrum with UAVs' management messages, and discuss the need for an efficient orchestration system. In this article, they propose a novel scheme, dubbed the aerial control system, which is based on separating the data plane from the control plane of UAVs, and pushing the latter to be performed in the air by UAVs. The solution provides an orchestration logic that takes advantage of the autonomous nature of UAVs to organize UAVs in one or several clusters. UAV-to-UAV communication enables spectrum reuse and avoids crowding the network with management messages, while dedicating more 5G spectrum for ensuring more bandwidth to the IoT through UAV-to-infrastructure communication.

The Group Management of Unmanned Aerial Vehicles in the Radio Silence Mode

Today due to the modern electronic countermeasures (ECM) progress for opening and interception of radio traffic channels, the group control task of unmanned aerial vehicles (UA V) in the radio silence mode is relevant as ever before. The aim of this work is to develop a UAV group control algorithm in radio silence. Group management refers to the optimization problem of actions of all group participants to achieve maximum group efficiency. In the case of lack of communication every UAV due to the onboard sensors identifies goals and other UA Vs in the detection area and operates according to its own optimum plan of target distribution, based on the available information. The optimally criterion considered as a function of two factors: the losses inflicted on the enemy when attacking the target, and the time spent to attack the target. Aviation blow to the group heterogeneous distributed ground targets is considered as subject. Fire resistance from the enemy in this work is not considered. Each target in the UAV detection area is given the value of the optimality criterion, based on the expert assessments. The search task for each UA V interpreted as goal attack virtual non-existent target, which has stochastic coordinates. For all targets and group members in the detection area, the UAV has a lot of plans of target distribution and acts in accordance with the preferred option. To estimate the effectiveness of the algorithm the simulation of shock operations in Matlab was performed for a UA V group that has been operating in the radio silence mode, and for a UAV group united by a common channel for the information exchange. The comparison of the simulation results showed the feasibility of applying the proposed algorithm.