Development of a complete UAV system using COTS equipment

The classification of drones - both military and civilian according to the relevant criteria - is presented. Block diagrams of a typical unmanned aerial vehicle and its power system are shown. Typically, a drone power system of the "micro", "mini" or "short range" category, according to the UVS international classification, is a set of DC / DC converters with a microprocessor control system. The power source for such aircraft is usually a battery, less often - fuel cells. During the flight, the engine speed is variable, and its change depends not only on changes in flight speed or direction, but also on weather conditions, such as wind, as the stabilization system constantly aligns the drone. This leads to the fact that the power supply system of such a device is actually a significant part of the time in transition condition. This leads to a significant content of the component of exchange energy that battery consumed which in turn will increase losses, and thus reduces the range of the unmanned aerial vehicle. The phenomenon of the occurrence of exchange power in the power supply systems of electric vehicles which powered from DC sources and specifically in the power supply system of an unmanned aerial vehicle is analyzed. The time diagrams of current, voltage, active and inactive components of power consumed from the mains power supply network of electric locomotive DE1 are illustrated. It can be seen that with a sharp change in the modes of operation of traction units there is a significant component of exchange power in the motor-network system. Such processes are typical for almost any electric vehicle and are associated with the presence of a significant number of reactive elements in the power supply systems, as well as frequent changes in load parameters. A block diagram of a typical unmanned aerial vehicle is presented. The unmanned aerial vehicle system consists of three parts: the air part, the unmanned aerial vehicle itself, the ground control station, which can be autonomous or manned, the control system, which provides communication and data transmission. The block diagram of the power system of a typical unmanned aerial vehicle is presented A simplified schematic diagram of the DC motor power supply system is presented. The relations for determining the amount of exchange power in the power supply system of an unmanned aerial vehicle are derived. It is concluded that to reduce the impact of this phenomenon, it is necessary to modify the power supply system by adding compensation units of inactive power component.

The unmanned aerial vehicle (UAV) is one of the mobile robots which has grown rapidly in popularity in recent years. UAVs have been used in various activities to convey important information on the aerial transportation system. However, an application to get real-time information from UAVs remains a challenging task. Therefore, this paper presents an integration system to optimise the use of UAVs for aerial surveillance. The proposed system explains the design and implementation a UAV system which consists of on-board and ground stations. The on-board system has the function to send UAV flight data, send aerial images and carry items using a gripper which equipped with sensors to detect obstacles. The ground station has the function to control UAV flights, receive and display UAV flight data and aerial images, display the attitude of the UAV and send commands to move the camera and gripper. Flight controllers in this system use non-linear complementary filter on SO(3) to estimate the attitude of the UAV and proportional-integral (PI) controller to stabilise the UAV flight. By providing the real-time acquisition data of the UAV, we believe this system can be a useful tool for many implementations using UAV.

Background. Development of radar complex for detection of air, sea, and ground objects, as well as determination of their distance, speed and geometric parameters with automated processing. Aim. Creation of an airborne side-scan radar complex with synthetic aperture mounted on an unmanned aerial vehicle. Methods. Application of digital signal processing methods for formation of radio holograms and extraction of information about objects. Use of algorithms for automatic processing and analysis of the obtained data in real time. Results. The structural-functional scheme of the X-band side-scan radar system consisting of an antenna, a receiving and transmitting unit, a container with a digital core and a micronavigation system is described. In high-resolution mode, a radar hologram formed on board and dropped via a communication channel to the control and processing station. Radar image formation and secondary processing is performed at the ground station in automatic mode. Conclusion. According to the results of the research it is shown that it is possible to realise real-time radar reception on board the carrier, as well as to install the considered airborne side-scan radar complex on an unmanned aerial vehicle together with an automated point of information processing and analysis.

This book provides fundamental principles, design procedures, and design tools for unmanned aerial vehicles (UAVs) with three sections focusing on vehicle design, autopilot design, and ground system design. The design of manned aircraft and the design of UAVs have some similarities and some differences. They include the design process, constraints (e.g., g-load, pressurization), and UAV main components (autopilot, ground station, communication, sensors, and payload). A UAV designer must be aware of the latest UAV developments; current technologies; know lessons learned from past failures; and they should appreciate the breadth of UAV design options. The contribution of unmanned aircraft continues to expand every day and over 20 countries are developing and employing UAVs for both military and scientific purposes. A UAV system is much more than a reusable air vehicle or vehicles. UAVs are air vehicles, they fly like airplanes and operate in an airplane environment. They are designed like air vehic...

Unmanned aerial vehicles (UAVs)-based applications, such as surveillance systems and wireless relays, are attracting increasing attention from academia and industrial fields. The high-performance aerial communication system is one of the key enablers for them. However, due to the low attenuation of radio waves in the air-to-ground channels, the interference between aerial and terrestrial communication systems would significantly deteriorate their communication performance and greatly limit the potential UAV applications. To address the problem, in this paper, the spectrum sharing strategy between a multiple UAV communication system, in which both UAVs and ground station (GS) are equipped with directional antennas, and terrestrial systems is proposed. The GS position is selected and the flyable areas of the UAVs using certain spectrum resources are defined in advance using prior knowledge from spectrum monitoring on terrestrial communication systems to minimize interference and maximize the flyable areas of the UAVs instead of the low-efficient dynamic channel sensing and allocation for interference elimination. The simulations are conducted through a case study of the spectrum sharing between a multi-UAV video transmission system and the terrestrial wireless local area network (WLAN) system in the 5.7GHz band. The simulation results show that thanks to the proposed system the entire area can be enabled for UAV flight.

As there has been an advancement in avionic systems in recent years, the enactment of unmanned aerial vehicles (UAV) has upgraded. As compared to a single UAV system, multiple UAV systems can perform operations more inexpensively and efficiently. As a result, new technologies between user/control station and UAVs have been developed. FANET (Flying Ad-Hoc Network) is a subset of the MANET (Mobile Ad-Hoc Network) that includes UAVs. UAVs, simply called drones, are used for collecting sensitive data in real time. The security and privacy of these data are of priority importance. Therefore, to overcome the privacy and security threats problem and to make communication between the UAV and the user effective, a competent anonymous mutual authentication scheme is proposed in this work. There are several methodologies addressed in this work such as anonymous batch authentication in FANET which helps to authenticate a large group of drones at the same time, thus reducing the computational overhead. In addition, the integrity preservation technique helps to avoid message alteration during transmission. Moreover, the security investigation section discusses the resistance of the proposed work against different types of possible attacks. Finally, the proposed work is related to the prevailing schemes in terms of communication and computational cost and proves to be more efficient.

In recent years, Unmanned Aerial Vehicles (UAVs) have attracted a lot of attention due to their flexibility and mobility. However, due to the increasingly complex environments faced by UAVs and the rising demands on UAV systems, traditional UAV control methods can no longer efficiently control the UAV under multi-constraint situations. Reinforcement Learning (RL), as an emerging robot control technology, is well suited to the needs of UAV systems in terms of its ability to interact with and learn from the environment. Therefore, RL-based UAV systems are gradually becoming a new trend in research. Nonetheless, as a new research field, it faces some challenges. To fully grasp the landscape of RL-based UAV systems, it is paramount to provide a comprehensive overview and analysis of the existing specific RL methods applied to UAV systems. In this survey, we first provide a comprehensive overview and summary of the application of RL in different UAV scenarios based on the classification of RL methods. After that, based on the existing relevant literature, we conduct a systematic analysis of the challenges and recent advancements when applying RL to UAV systems. Finally, we discuss the potential research directions for RL-based UAV systems.

In this paper, a quadcopter unmanned aerial vehicle (UAV) system based on neural-network enhanced dynamic inversion control is proposed for multiple real-world application scenarios. A sigma-pi neural network (SPNN) is used as the compensator to reduce the model error and improve the system performance in the presence of the uncertainties of UAV dynamics, payload, and environment. Besides, we present a technical framework for fast and robust implementation of multipurpose UAV systems and develop a testbed for the evaluation of UAV control system by using a high-precision optical motion capture system. Both simulation results and experiment results demonstrate that the SPNN can reduce the inversion errors related to UAV parameter uncertainties as well as tracking errors related to unknown disturbances and unmodeled dynamics. With the help of an online neural network (NN) learning mechanism, the entire system can achieve much higher accuracy in attitude and trajectory control than that achieved by conventional proportional-integral derivative based control systems under varying flight conditions.

The purpose of this work is the analysis of the power supply system of unmanned aerial vehicle. One of the most important tasks of this system is to ensure the smallest possible losses in order to achieve greater endurance of the aircraft, which means – the ability to complete the mission. The presence of an inactive component of consumed power obviously reduces the efficiency of the entire unmanned aerial vehicle. Considering also that due to the influence of wind, speed changes and other factors, the power system spends a significant amount of time in the transition mode, the impact of this phenomenon becomes even more significant. Thus, the phenomenon of the occurrence of exchange power in the power supply system of an unmanned aerial vehicle is analyzed. One of the most common solutions for unmanned aerial vehicles is the use of a BLDC motor, which is a further development of DC motors and was created with the aim of improving their basic characteristics. This type of engine has gained its popularity due to numerous advantages: high reliability, efficiency, speed and others. The principles of control of the BLDС engine are given. The unmanned aerial vehicle power supply system, built on the basis of a buck converter and a bridge inverter, was analyzed. An equivalent circuit of the converter is built, taking into account the losses in the electric circuit. On its basis the relations for determining the value of exchange power in the power supply system are derived. With the help of these expressions, it is possible to determine the value of the exchange energy at an arbitrary time interval in the real power supply system of the aircraft. A model of the power supply system of an unmanned aerial vehicle with a BLDC engine was built in the Matlab Simulink software environment. A time diagram is obtained, on the basis of which it is possible to draw a conclusion about the content of exchange power in the converter circuit. To minimize this phenomenon, it is necessary to develop a compensation system or an intelligent control system.

Aircraft tracking plays a key and important role in the Sense-and-Avoid system of Unmanned Aerial Vehicles (UAVs). This paper presents a novel robust visual tracking algorithm for UAVs in the midair to track an arbitrary aircraft at real-time frame rates, together with a unique evaluation system. This visual algorithm mainly consists of adaptive discriminative visual tracking method, Multiple-Instance (MI) learning approach, Multiple-Classifier (MC) voting mechanism and Multiple-Resolution (MR) representation strategy, that is called Adaptive M <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> tracker, i.e. AM <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . In this tracker, the importance of test sample has been integrated to improve the tracking stability, accuracy and real-time performances. The experimental results show that this algorithm is more robust, efficient and accurate against the existing state-of-art trackers, overcoming the problems generated by the challenging situations such as obvious appearance change, variant surrounding illumination, partial aircraft occlusion, blur motion, rapid pose variation and onboard mechanical vibration, low computation capacity and delayed information communication between UAVs and Ground Station (GS). To our best knowledge, this is the first work to present this tracker for solving online learning and tracking freewill aircraft/intruder in the UAVs.

Autonomous formation flight has been a fast growing research area during the last decade. Unmanned aerial vehicles (UAVs) can achieve a wide range of benefits from formation flight, such as fuel saving and aerial refueling. In this paper, the development of a small UAV system, called Swallow UAV system, as testbed of formation flight, is presented. Swallow UAV system includes Swallow UAV itself and a Hardware-In-the-Loop Simulation Environment (HILSE). Swallow UAV is a fixed wing, pusher-type, electric motor driven aircraft with 1.4 meter wing span. Its avionics system includes an onboard computer and a sensor system with GPS, IMU, air data sensor, and motor monitoring unit to provide position, velocity, inertial data, and system health. Communications between UAVs and the ground control station (GCS) are conducted by wireless modem. A fuzzy navigation and control system (FNCS) is developed for the waypoint navigation and attitude control of the aircraft. GPS velocity based pseudo attitude and fuzzy logic control are applied to FNCS for attitude estimation and fast implementation of controllers. HILSE is built to verify FNCS with onboard computer on the ground. X-Plane flight simulator is applied to simulate aircraft dynamics and output sensor data. GCS software, built with data distributor, transmits these data to the onboard computer and receive control signal from it so the onboard computer can control the aircraft in X-Plane. HILSE can perform pre-flight test for software debug, which improves safety and efficiency of flight test. The design of Swallow UAV is verified by flight test and the result shows that it has sufficient flight performance with waypoint navigation and attitude control capability to be used as a formation flight testbed.

In this paper, we develop an alternative navigation system for Unmanned Aerial Vehicle (UAV) in Global Positioning Systems (GPS)-denied environment. We use two image inputs, one is acquired with an on-board camera placed on the UAV (which is the large-area image) and the other is from satellite images (which is small known image) with GPS information. We use a convolutional neural network (CNN) architecture based on Oxford’s Visual Geometry Group network (VGG-16) and utilize normalized variant mutual information between these two images to obtain position of the UAV. Satellite images are labelled and given to the UAV. When GPS information is lost, our algorithm starts to function and images from UAV camera are searched whether satellite image is seen by cameras on UAV image or not. If the UAV is in that area, our algorithm finds the GPS information from satellite image data.

This work presents a tracking system for autonomous unmanned aerial vehicle (UAV) and any ground vehicle using global positioning system (GPS) and general packet radio service (GPRS). A Google form is created and a Google spreadsheet is set as destination location to store Google form responses on ground station. Whenever UAV is flying autonomously, GPS finds its current location (latitude and longitude). Thereafter, GPRS sends hypertext transfer protocol (HTTP) request which consists of the current location of a UAV and submits a response in Google form and Google spreadsheet. A custom function is added in a Google spreadsheet to monitor the path of an UAV on static Google map using Google Apps Script (GAS).

Wireless communication with unmanned aerial vehicle (UAV) has attracted much attention due to its flexibility and low-cost in providing wireless connectivity. In this article, we investigate the spectrum sharing between UAV and terrestrial wireless communication. Two scenarios are considered in this work. Scenario 1: the UAV is energy sufficient to transmit the required data. In this case, our objective is to minimize the time that is needed to complete data transmission. Scenario 2: the battery of the UAV is energy insufficient. In this case, the goal becomes maximizing the size of data that can be transmitted. Different scenarios require different placement of the UAV. When the UAV flies towards the primary user (PU), the sensing result will be more accurate and more opportunities can be utilized to transmit data. However, the interference to primary receiver (PR) and the propulsion energy due to UAV's movement will be increased. In this article, the sensing performance, the power allocation and the UAV's position are jointly optimized to satisfy different requirements of the UAV system. To efficiently utilize the licensed spectrum, a hybrid transmission mode is proposed for the UAV system, in which sensing and power control are jointly employed to protect the PR. Then, efficient iterative algorithms are proposed to solve the optimization problems. Simulations results show that proposed designs can significantly reduce the time that is required to complete data transmission in energy sufficient scenario and enhance the size of data that can be transferred in energy insufficient scenario.

This work is devoted to the detection of inconspicuous flying objects (unmanned aerial vehicles) by ground-based means. The analysis of traditional methods of solving the problem under consideration, based on the use of active radar, is carried out. A list of characteristics is formulated, including the control systems of modern unmanned aerial vehicles, which cause difficulties in traditional approaches to their detection. A study has been conducted on the possibility of using a passive radar method based on recording changes in the radio signal of a spacecraft of the Starlink satellite network to detect inconspicuous unmanned aerial vehicles crossing the radiation zone "Spacecraft – Earth (ground station)". When justifying the possibility, the following are given: characteristics and technology of the Starlink satellite network; estimates of the magnitude of changes in the main characteristics of the radio signal (phase shift, Doppler frequency shift, received signal power) depending on the time the unmanned aerial vehicle crosses the monitoring zone of the radio signal from the spacecraft by ground means. Preliminary requirements for a system for detecting inconspicuous unmanned aerial vehicles based on recording changes in the radiation characteristics of the Starlink satellite network have been formed. A detailed study of the proposed approach to detecting unmanned aerial vehicles using a ground-based signal reception system from a spacecraft of the Starlink satellite network requires the creation of a complete mathematical model of the process, which must be based on a rigorous approach to solving the diffraction problem.