Ground Control Station Research Articles

Extremum Seeking-Based Radio Signal Strength Optimization Algorithm for Hoverable UAV Path Planning

For the safe autonomous operations of unmanned aerial vehicles (UAVs) and ground control stations (GCS), including autonomous battery replacement, wireless power transfer, and more, the precise landing of UAVs on GCS is essential. Accurate landing is only possible when the link capacity strength exceeds a certain threshold, but this is often disturbed due to complex terrain. To address this, we developed an extremum seeking (ES)-based radio signal strength optimization (RSSO) algorithm, ES-RSSO, designed to find the optimal positions of the UAV using radio communication signals. This ensures energy-efficient path planning while guaranteeing the minimum received signal strength indication (RSSI) capacity. This algorithm is particularly useful in obstacle-rich environments, where UAVs are limited in power resources. Simulation results demonstrate a 2.37% decrease in the mean, a 62.08% improvement in variance, and a 3.72% decrease in the integration strength of the link capacity when ES-RSSO is applied. These results confirm that the RADIO.rssi maintenance ability remains above a critical boundary level, supporting robust communication links and energy-efficient path planning. Throughout the study, we showed how, in many cases, simply moving the UAV a few meters can significantly improve the communication link.

Robust Optimization Models for Planning Drone Swarm Missions

This article presents methods of planning unmanned aerial vehicle (UAV) missions in which individual platforms work together during the reconnaissance of objects located within a terrain. The planning problem concerns determining the flight routes of a swarm, where each UAV has the ability to recognize an object using a specific type of sensor. The experiments described in this article were carried out for drone formation; one drone works as a swarm information hub and exchanges information with the ground control station (GCS). Numerical models for mission planning are presented, which take into account the important constraints, simplifying the description of the mission without too much risk of losing the platforms. Several types of objective functions were used to optimize swarm flight paths. The mission models are presented in the form of mixed integer linear programming problems (MILPs). The experiments were carried out on a terrain model built on the basis of graph and network theory. The method of building a network on which the route plan of a drone swarm is determined is precisely presented. Particular attention was paid to the description of ways to minimize the size of the network on which the swarm mission is planned. The presented methods for building a terrain model allow for solving the optimization problem using integer programming tasks.

UAV Hunter: A Net-Capturing UAV System with Improved Detection and Tracking Methods for Anti-UAV Defense

The abuse of UAVs poses a potential risk to social security, necessitating the investigation of anti-UAV methods to safeguard critical areas. However, the existing UAV countermeasures face challenges such as high environmental impact, restricted spatial deployment, and low cost-effectiveness. To address these limitations, we developed a novel anti-UAV system known as UAV Hunter, which adopts an airborne tether-net capture device with visual aids to counter unauthorized UAVs. This system employs an “Anti-UAV with UAV” scheme, comprising a ground control station and a net-capturing UAV. The operator utilizes the ground control station to determine the mission area and flight path and then controls the flight of the net-capturing UAV. During flight, the net-capturing UAV leverages its dual-mode sensor to continuously monitor the target area. Simultaneously, the onboard computer executes a UAV detection and tracking algorithm to search for unauthorized UAVs in real time. The results are relayed to the operator in real time, facilitating precise adjustments for the net-capturing UAV to launch the rope net accurately. The system successfully realizes the functions of dual-mode real-time detection and tracking, precise net capture, and efficient integrated control. Compared with existing methods, the developed system exhibits accurate recognition, rapid action, diverse application scenarios, and an enhanced human–machine interaction experience. Test results in the open environment further validate the feasibility and functional integrity of the system, demonstrating its capability to effectively capture low-altitude unauthorized UAVs.

Prototype for Multi-UAV Monitoring–Control System Using WebRTC

Most unmanned aerial vehicle (UAV) ground control station (GCS) solutions today are either web-based or native applications, primarily designed to support a single UAV. In this paper, our research aims to provide an open, universal framework intended for rapid prototyping, addressing these objectives by developing a Web Real-Time Communication (WebRTC)-based multi-UAV monitoring and control system for applications such as automated power line inspection (APOLI). The APOLI project focuses on identifying damage and faults in power line insulators through real-time image processing, video streaming, and flight data monitoring. The implementation is divided into three main parts. First, we configure UAVs for hardware-accelerated streaming using the GStreamer framework on the NVIDIA Jetson Nano companion board. Second, we develop the server-side application to receive hardware-encoded video feeds from the UAVs by utilizing a WebRTC media server. Lastly, we develop a web application that facilitates communication between clients and the server, allowing users with different authorization levels to access video feeds and control the UAVs. The system supports three user types: pilot/admin, inspector, and customer. Our research aims to leverage the WebRTC media server framework to develop a web-based GCS solution capable of managing multiple UAVs with low latency. The proposed solution enables real-time video streaming and flight data collection from multiple UAVs to a server, which is displayed in a web application interface hosted on the GCS. This approach ensures efficient inspection for applications like APOLI while prioritizing UAV safety during critical scenarios. Another advantage of the solution is its integration compatibility with platforms such as cloud services and native applications, as well as the modularity of the plugin-based architecture offered by the Janus WebRTC server for future development.

Improving communication between can-sized satellite and ground control station for accuracy of data acquisition

Improving communication between can-sized satellite and ground control station for accuracy of data acquisition

Analysis of User Interfaces for Ground Control Stations of Unmanned Aerial Vehicles

Introduction. In the modern world, software (SW) is updated daily, particularly for ground control stations (GCS) of unmanned aerial vehicles (UAVs). These systems ' user interfaces (UI) ensure operator interaction with the drone, flight control, mission planning, and realtime data acquisition. These interfaces must be functional, convenient, and intuitive, allowing operators to perform their tasks effectively. Examining global experience allows for an evaluation of existing systems and the identification of areas for improvement. Important aspects include creating intuitive UIs to prevent information overload, ensuring situational awareness, adapting to extreme conditions, and integrating with other systems. The use of virtual and augmented reality technologies, as well as artificial intelligence, can enhance the functionality and convenience of GCS. Such analysis will help in creating safe, efficient, and reliable systems for UAV control. The purpose of the paper is to investigate and conduct a comprehensive analysis of existing user interfaces of software for UAV ground control stations, focusing on their functional capabilities and ease of use. Methods. The following methodological tools were used: concepts of intellectualization of information technologies, the theory of intelligent control, the methodology of building autonomous systems, decision-making theory, and artificial intelligence theory. Results. A review of global experience in user interface development was conducted. The UIs of each of the studied software were analyzed, and their functional capabilities were assessed, identifying their strengths and weaknesses. Comparative tables of interface products were compiled based on their functional capabilities and UI usability levels. Generalized recommendations were prepared for creating a unified interface that combines the best features of existing solutions and addresses their shortcomings. Conclusions. The analysis of GCS UI design for UAVs showed that all systems have strengths and weaknesses. The UI of the Mission Planner software has the most extensive capabilities, but it also requires improvement. Future development should add roles for military pilots and operators, develop a more intuitive and user-friendly interface that meets user needs, and simplify SW settings. For working in extreme conditions, the interface needs to be optimized. Enhancements in data visualization will help make information clear and easy to understand, which is critically important in fast-paced and dangerous situations. Keywords: user interface, ground control station, UAV, virtual reality, augmented reality.

Acquisition of Flight Data from Mini Unmanned Aerial Systems

Swift progress in unmanned aerial vehicle (UAV) system technology mandates effective real-time monitoring and accurate flight data capture for building an optimum target-based cutting-edge UAVs. In the current epoch of modern-UAV era, small size and mission-oriented UAV prototypes are increasingly pervasive. This study highlights the design of a data acquisition target-based mini-UAV and introduces a novel telemetry software solution to safe and reliable communication between mini-UAV and ground control station (GCS). The primary aim is to demystify the proposed wireless communication software solution on mini-UAV capability in obtaining and managing comprehensive flight data. While creating the appropriate target-based mini-UAV prototype architecture, the features that we aim to realize for the UAV components are addressed with a system approach and the component selection is presented in detail. The integration point of the selected components is conveyed in general terms. Thus, a guiding resource for future UAV studies will be presented. Then, the processes of obtaining the flight data of mini-UAVs will be addressed. At this point, the design logic of the required commands and background software will be conveyed. Obtaining the flight data of mini-UAVs will provide important scientific contributions to the literature in terms of aviation research and safety analysis. Obtaining the flight data of mini-UAVs will meet the data set needs for flight safety improvements and air traffic management optimization studies. A general analysis of the flight parameters obtained as a result of obtaining the flight data will be performed, the predictability of the parameters will be evaluated, and the analysis of the flight phases will be performed by presenting the relationships of the parameters according to the flight scenarios and the sections taken from the parameter set in the study. This study can be considered as a concrete example of situational monitoring of UAVs.

Smart surveillance: deploying drones for efficient and adaptive monitoring solutions

The growing need for real-time and adaptable surveillance solutions has prompted the investigation of cutting-edge technologies within security and monitoring frameworks. This paper introduces an innovative surveillance approach that utilizes drones to improve situational awareness and operational efficiency across various domains, including public safety, border security, and environmental monitoring. The proposed system integrates autonomous drones equipped with sophisticated imaging capabilities, data processing techniques, and machine learning algorithms, facilitating real-time monitoring, threat identification, and comprehensive data analysis. Notable features of this system include autonomous path planning, the ability to adapt to changing environmental conditions, and effective communication with ground control stations. By merging drone technology with AI-enhanced analytics, this approach provides a scalable and cost-efficient surveillance solution that minimizes the need for human intervention while enhancing accuracy and response times. In this paper, we detail the design, implementation, and performance assessment of our system, underscoring its potential to transform conventional surveillance practices.

Implementation Of Error Checking In Data Security In Ground Control Station And UAV Communications

Implementation Of Error Checking In Data Security In Ground Control Station And UAV Communications

Authentication communication by using visualization cryptography for UAV networks

Utilizing unmanned aerial vehicles (UAVs) to support V2X requirements leverages their versatility and line-of-sight communication. Our prior work explored a multi-agent learning approach for resource optimization, maximizing task offloading while maintaining QoS. This paper focuses on securing UAV communication, particularly authentication. Traditional methods are often unsuitable due to UAV limitations. We propose a novel authentication mechanism for a single ground control station (GCS) interacting with multiple UAVs across flight sessions. The system utilizes a key generation method based on chaotic maps to create unique flight session keys for each pre-defined flight plan. These keys, along with flight plans, are registered in a secure database. During flight, the GCS verifies UAV identity by employing the flight session key and corresponding flight plan for message authentication. This approach reduces computational and communication overhead compared to traditional certificate exchanges and asymmetric cryptography, which are energy-intensive for UAVs. While not a comprehensive security solution, this method provides an initial layer of protection for the UAV network.

A swarm anomaly detection model for IoT UAVs based on a multi-modal denoising autoencoder and federated learning

The widespread application of unmanned aerial vehicle (UAV) swarms has posed unique challenges for anomaly detection. Multi-modal noise from multi-source heterogeneous sensors during UAV swarm communication affects data quality, and limited data sharing between different UAV organisations restricts training a unified anomaly detection model. To address these problems, this study proposes a UAV swarm anomaly detection model based on a multi-modal denoising autoencoder and federated learning (L-MDAE). First, L-MDAE simulates noise by adding perturbations to the original data during UAV swarm communication. Second, according to the characteristics of UAV data noise, this study designs a new MSE loss function (normalised mean square error, NMSE) based on the normalised correlation coefficient. Furthermore, heterogeneous neural networks with NMSE are constructed to enhance the multi-modal noise–removal capability of the model. Finally, this study considers the UAV control node as the client and the ground control station as the server. Using a federated learning mechanism, L-MDAE is trained on a client dataset, and its parameters are integrated and distributed on the server. In this way, each UAV can effectively detect abnormal data using L-MDAE. Experimental results on five datasets, including ALFA, TLM and ITS, demonstrate that L-MDAE outperforms baseline and related models. When using ALFA, L-MDAE achieved an accuracy of 0.9919 and a swarm anomaly detection accuracy of 0.9901, approximately 2% higher than that of the baseline model.

Developing a custom communication protocol for UAVs: Ground control station and architecture design

Robots have become a prominent research topic across various application domains in recent decades. Additionally, unmanned aerial vehicles (UAVs) are extensively used in both the military and commercial sectors, substantially reducing transaction costs and enhancing safety. Researchers have addressed secure control and communication protocols between software, firmware, and hardware components. This study focuses on the design of three critical elements: the hardware architecture, the software ground control station (GCS), and the firmware tasks within the UAV embedded system. These components are interconnected via an enhanced MAVLink protocol (EMP). Furthermore, various sensors are integrated into the UAV's peripheral devices. We discuss flight control (FC) approaches, such as proportional-integral-derivative (PID) control and the Kalman filter (KF), detailing the process of the hovering algorithm. Additionally, we explain how access is messaged and how message commands are implemented at the protocol layer. We propose a large-scale UAV system architecture suitable for commercial and military applications, supported by a real-life scenario. Experimental results demonstrate the effectiveness and efficiency of the UAV in outdoor activities. Our findings confirm that the proposed UAV architecture is a robust and efficient system in practical applications.

Development of Ground Control Station for Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) have emerged as important tools in various industries, from military research to civilian applications such as agriculture, disaster management and research. This paper examines the technological development of GCS and current state-of-the-art developments, including advances in hardware, software, and human-machine interfaces. Through a systematic review of recent research, we identify key policy considerations, performance criteria, and challenges associated with GCS development. In addition, we explore autonomy, artificial intelligence integration, cybersecurity, interoperability standards, and other development trends that are changing the UAV industry landscape. Combining insights from academic literature, industry reports, and technology developments, this review provides a comprehensive understanding and new idea of the state of GCS technology and valuable perspectives on future research directions and practical applications in UAV systems.

Joint optimization of communication and mission performance for multi-UAV collaboration network: A multi-agent reinforcement learning method

In emergency rescue, target search and other mission scenarios with Unmanned Aerial Vehicles (UAVs), the Relay UAVs (RUs) and Mission UAVs (MUs) can collaborate to accomplish tasks in unknown environments. In this paper, we investigate the problem of trajectory planning and power control for the MU and RU collaboration. Firstly, considering the characteristics of multi-hop data transmission between the MU and Ground Control Station, a multi-UAV collaborative coverage model is designed. Meanwhile, a UAV control algorithm named MUTTO is proposed based on multi-agent reinforcement learning. In order to solve the problem of the unknown information about the number and locations of targets, the geographic coverage rate is used to replace the target coverage rate for decision making. Then, the reward functions of two types of UAVs are designed separately for the purpose of better cooperation. By simultaneously planning the trajectory and transmission power of the RU and MU, the mission target coverage rate and network transmission rate are maximized while the energy consumption of the UAV is minimized. Finally, numerical simulations results show that MUTTO can solve the UAV network control problem in an efficient way and has better performance than the benchmark method.

Mission-critical UAV swarm coordination and cooperative positioning using an integrated ROS-LoRa-based communications architecture

Over the recent years unmanned aerial vehicles (UAVs) have been utilized extensively in mission-critical operations, especially as it relates to disaster management scenarios. Clearly, during these missions, the UAVs should be able to communicate effectively (amongst themselves and with the ground control station (GCS)) in order to transmit and receive commands and other related information. Moreover, accurate positioning is paramount during this type of operations. This has motivated the exploration of a number of alternative navigation methods to address robustness issues that arise when the global positioning system (GPS) becomes unavailable, due to GNSS disruption or sensor malfunction. This work addresses these issues by initially developing and implementing an integrated LoRa-ROS-based (long range communication - robot operating system) system for UAV-to-X communications. Subsequently, it presents a novel cooperative positioning approach, where a group of autonomous UAVs employ various algorithms (detection, tracking, communication, and localization) for cooperative positioning in order to counter any GPS/sensor malfunction. For evaluation purposes, a prototype multi-agent system is designed and implemented, utilizing the proposed integrated ROS-LoRa-based communication architecture, as well as sensor (inertial measurement unit - IMU) fusion. Specifically, LoRA mesh networking (using a custom printed circuit board - BALORA), is incorporated to maintain communication and distribute the sensor information between the UAVs. The prototype of the proposed communications architecture and cooperative relative positioning system (CRPS) is subsequently tested in a real-world environment, demonstrating the feasibility and effectiveness of the proposed communications solution, as well as the robust and accurate localization that is analogous to the ground truth (GPS+IMU).

GreatBlue: a 55-Pound Vertical-Takeoff-and-Landing Fixed-Wing sUAS for Science; Systems, Communication, Simulation, Data Processing, Payloads, Package Delivery, and Mission Flight Performance

As small, uncrewed systems (sUAS) grow in popularity and in number, larger and larger drone aircraft will become more common–up to the FAA limit of 55 pound gross take-off weight (GTOW) and beyond. Due to their larger payload capabilities, longer flight time, and better safety systems, autonomous systems that maximize CFR 14 Part 107 flight drone operations regulations will become more common, especially for operations such as imagery or other data collection which scale well with longer flight times and larger flight areas. In this new paper, a unique all-electric 55-pound VTOL transition fixed-wing sUAS specifically engineered for scientific data collection named “GreatBlue” is presented, along with systems, communications, scientific payload, data collection and processing, package delivery payload, ground control station, and mission simulation system. Able to fly for up to 2.5 hours while collecting multispectral remotely-sensed imagery, the unique GreatBlue system is shown, along with a package delivery flight example, flight data from two scientific data collection flights over California almond fields and a Utah Reservoir are shown including flight plan vs. as-flown.

Using VR to Validate and Visualize MBSE‐Designed Interfaces

AbstractSeveral unique challenges arise in the new field of integration between Model‐Based Systems Engineering (MBSE) models and game‐based digital twin visualizations. First, no known standardized interfaces between the MBSE model and game engine visualization are defined, which can lead to custom or stove‐piped solutions. Additionally, visualizing digital twin models in true to life scale is insufficient with typical desktop computers. The Bi‐Directional Interface Requirements Operational System Test (BIFROST) prototype, funded by the US Army Program Executive Office (PEO) Aviation, seeks to address these challenges.Progress of the BIFROST prototype is covered in the paper. The prototype aims to determine the feasibility and challenges of validating interfaces through visualizing changes to an MBSE model in a 3D game engine. Research was performed to visualize part of an uncrewed aircraft system ground control station in 3D using the Unity game engine. A Mission Control Architecture MBSE model, developed by PEO Aviation, is used to drive the digital twin of the ground control station through a set of virtual reality (VR) controls. Users can visualize, analyze, and test the human‐machine interaction of the 3D models in VR prior to real‐world system changes. This paper presents the recommended interfaces between the MBSE model and 3D engine, lessons learned, and future research areas.

AUTHENTICATION OF WIRELESS SYSTEMS BASED ON A DRONE SWARM AS A COMPONENT OF THE 5G RADIO ACCESS NETWORK ARCHITECTURE

Background. When establishing security measures for telecommunication networks involving unmanned aerial vehicles (UAVs), characteristics such as high scalability, device diversity, and high mobility should be considered. Authentication is a fundamental property that allows a UAV network to establish secure communication between its core components. Authentication also protects the UAV network from attackers impersonating legitimate UAVs. UAV authentication can further secure the communication channel by preventing impersonation and replay attacks. The design of UAV access control schemes, such as authorization and authentication mechanisms, remains a challenging research problem in UAV networks. The network becomes even more complicated when it interacts with a multitude of UAVs, called a swarm. A swarm by its very nature has a dynamic structure, and this raises the issue of unreliable constraints on UAVs in its composition. A standardized solution for the authentication of a single drone using the new 5G radio network (NR) is known, but for a swarm of drones, this is an open field of research. Per-UAV authentication key sharing as described in 5G NR does not scale across groups of UAVs. Objective. The purpose of this work is to conduct an analytical review and consider approaches to creating procedures for the authentication of a swarm of UAVs/drones with wireless equipment on board for the 5G NR network, taking into account the features of swarm formation and the very requirements for 5G authentication. Methods. Analysis of factors affecting the quality of provision of telecommunication services using UAVs in fifth generation networks. Analysis of well-known publications dedicated to the implementation of 5G networks and the use of drones in them. Comparing the implementation of UAV authentication procedures with on-board wireless equipment in the 5G network. Results. The widespread use of small UAVs, as well as the large expansion of wireless 5G networks, requires new security measures to prevent unauthorized access to sensitive data. Identification and Authentication for a mobile operator's network using drones allows for secure communication between its main components. This makes it possible to recognize the very drones that participate in the formation of such a network. Drone authentication often protects the communication channel by preventing replay attacks. The development of drone radio access control mechanisms, such as authorization and authentication mechanisms, remain relevant researches for the construction of promising radio access networks involving UAVs. It has been confirmed that the introduction of special group procedures for the authentication of a swarm of drones in the 5G network can significantly improve the quality of the provision of telecommunication services. Conclusions. When working with a swarm of drones, in addition to the usual problems with encryption and authentication (within the swarm and for communication between the swarm and the ground control station), there are additional problems related to the constant change in the composition of the swarm and its hovering position: drones can join or leave a swarm. Depending on the swarm management structure, a different method of authentication will be needed, which makes it difficult to unify such procedures for a swarm of drones. Authentication procedures for a swarm of drones in 5G can be implemented through the following approaches: individual authentication, when each drone as a member of the swarm undergoes authentication with one NR 5G ground station; you can consider such an approach as authentication of a group of IoT devices, if the traffic of the swarm is very limited; group authentication through a leader drone that communicates with swarm members and the 5G operator's network; group distributed authentication through edge drones. Group authentication via a drone leader is presented, where authentication is performed through a mechanism based on distributed delegation to reduce the service traffic directed to the 5G operator's core network. Here, legitimate drones are authorized as proxy delegated signers to perform authentication on behalf of the underlying network. Group distributed authentication through boundary drones is considered, which offers more solutions than the case of authentication through a leader drone. Here, a solution is possible for several cases at once, for example, authentication of new drones (entering the swarm or leaving the swarm) and merging two separate drone swarms.

Algorithm for measuring parameters of radio link of an unmanned aircraft in fpv mode of the centimeter frequency range

The mass use of unmanned aerial vehicles (UAVs) in the mode of remote control "from the first person" (First Person View, FPV) in combat operations radically changes the picture of modern war. Their use makes it possible to damage or destroy enemy equipment, the cost of which is hundreds of times higher than the cost of UAVs. To successfully perform the UAV flight mission in FPV mode, it is necessary to ensure stable radio communication of the UAV with the ground control station (GSC). In the work to organize a radio line between the GSC and the UAV, it is proposed to use radio lines of the centimeter frequency range. At the same time, at the stage of flight mission planning, the UAV operator needs to have information about the parameters of the receiving and transmitting devices of the unmanned aerial vehicle complex (UAVС) in order to calculate the maximum flight range. The purpose of the work is to develop an algorithm for measuring parameters of the radio link of an unmanned aerial vehicle in the FPV mode of the centimeter frequency range. The use of this information will allow the UAVC operator to create a flight map and prepare for a combat mission. The material presented in the article contains practical value for UAV operators and can be used in the organization and planning of the flight mission of multi-rotor UAVs of the tactical level at a given distance. Also, the material can be used by UAV service units for the purpose of checking the technical parameters of the radio link between the UAV and GSC and the optical systems installed on board the UAV (video cameras, thermal imaging cameras, etc.).

Identity Authentication for Ground Control Station Based on MmWave MIMO Channel Sparsity

Identity Authentication for Ground Control Station Based on MmWave MIMO Channel Sparsity