Computer Modelling of Autonomous Satellite Navigation Characteristics on Geostationary Orbit

Satellite systems are a fast-developing and broad field of study. The use of global navigation satellite systems for relatively autonomous spacecraft navigation holds a lot of interest for researchers. It is extremely expensive to research space applications as live experiments. Therefore, computer modelling comes in handy when there is a need to analyze important factors in space environment. The chapter describes the radionavigation field model that uses the off-nadir satellites. This model allows estimation of the availability and accuracy characteristics of autonomous satellite navigation in space up to the geostationary orbit in order to provide the necessary research data.

Information Technology for the Coordinated Control of Unmanned Aerial Vehicle Teams Based on the Scenario-Case Approach

The authors present a dynamic scenario-case approach to coordinated control of heterogeneous ensembles of unmanned aerial vehicles, which use coordination patterns of activity in similar situations described as spatial configurations affected by observed events. The method of obtaining deviations for approximate spatial configurations, which allows obtaining elements of the safe vehicle's trajectories. The method of qualitative safety assessment is presented. It uses a soft level topology to obtaining blurred boundaries of dynamic safety domains using fuzzy soft level sets and allows finding suitable compensations of vehicles' activity scenarios that can both keep the spatial configuration and satisfy all safety restrictions. The authors demonstrate that the proposed approach significantly reduces the computational complexity of problem solving and provides the acceptable performance.

Data Science Tools Application for Business Processes Modelling in Aviation

Successful business involves making decisions under uncertainty using a lot of information. Modern modeling approaches based on data science algorithms are a necessity for the effective management of business processes in aviation. Data science involves principles, processes, and techniques for understanding business processes through the analysis of data. The main goal of this chapter is to improve decision making using data science algorithms. There are sets of frequently used algorithms described in the chapter: linear, logistic regression models, decision trees as a classical example of supervised learning, and k-means and hierarchical clustering as unsupervised learning. Application of data science algorithms gives an opportunity for deep analyses and understanding of business processes in aviation, gives structuring of problems, provides systematization of business processes. Business processes modeling, based on the data science algorithms, enables us to substantiate solutions and even automate the processes of business decision making.

Critical Aviation Information Systems

This chapter is devoted to developing formalization methods for identification and security objects of critical information infrastructure (CII) in civil aviation. The analysis of modern approaches to the CII identification was carried out that gave a possibility to determine weaknesses and to formalize a scientific researches task. As a result, the unified data model was developed for formalizing the process of a list of CII objects forming in certain field and at the state level. Moreover, the specialized technique was developed. Besides, the identification method was proposed, and it gives a possibility to determine elements of CII field, mutual influences, and influence on functional operations of critical aviation information system. Furthermore, special software was developed and implemented that can be useful for CII elements identification and also for determining its influences on functional operations. Also, the basic aspects of cybersecurity ensuring for identified critical aviation information system were described in this chapter.

Analysis and Optimization of Diagnostic Procedures for Aviation Radioelectronic Equipment

In this chapter, the authors present the questions of aviation radioelectronic equipment operation. The structure of operation system is considered based on processes approach with adaptable control principles usage. Operation system contains processes of diagnostics and health monitoring. The authors consider the direct problem of efficiency estimation for diagnostics process, and main attention is paid to probability density function calculation for diagnostics duration. Simulation results were used for adequacy testing of these calculations. The authors also take into account the possibility of first and second kind errors presence. The inverse problem for diagnostics is defined and solved for mathematical expectation of repair time. In general case, the inverse problem can be solved for seven options of optimization.

Guidance Algorithm for Unmanned Aerial Vehicles on a Basis System of Technical Viewing

The chapter considers a description of developed control system for a group of unmanned aerial vehicles (UAV) that has a software capable to continue the flight in case of failures by using alternative control algorithms. Control system is developed on vision system by using methods of image recognition. Grouped coordinated flight of UAVs can significantly improve the performance of surveillance processes, such as reconnaissance, image recognition, aerial photography, industrial and environmental monitoring, etc. But to control a group of UAVs is a quite difficult task. In this chapter, the authors propose a model that corresponds to the principle of construction by the leading UAVs. In the case of using this model, the parameters of the system motion are determined by the direction of motion, the speed, and the acceleration of the UAVs' driving. The control system based on the methods of image recognition expands the possibilities of coordinating the group of UAVs.

Using Unmanned Aerial Vehicles to Solve Some Civil Problems

The widespread use of unmanned aerial vehicles (UAVs) is currently a recognized trend. UAVs find their application in various sectors of the economy. In the chapter, based on extensive literature analysis, the possibilities of using UAVs for non-military applications are considered. The design features of various UAVs, their control features, energy requirements, and safety-related problems are considered. Particular attention is paid to public opinion related to the use of UAVs. The possibilities of using UAVs in power engineering, agriculture, for controlling traffic, for goods transporting, for controlling the means of railway transport, for first aid to people under various extreme conditions, as well as for some other applications are being explored. The UAV parameters are analyzed, which must be provided for their use in each specific case, while ensuring the minimization of the necessary financial resources.

Artificial Neural Network for Pre-Simulation Training of Air Traffic Controller

In this chapter, the four layers neural network model for evaluating correctness and timeliness of decision making by the specialist of air traffic services during the pre-simulation training has been presented. The first layer (input) includes exercises that cadet/listener performs to solve a potential conflict situation; the second layer (hidden) depends physiological characteristics of cadet/listener; the third layer (hidden) takes into account the complexity of the exercise depending on the number of potential conflict situations; the fourth layer (output) is assessment of cadet/listener during performance of exercise. Neural network model also has additional inputs (bias) that including restrictions on calculating parameters. The program “Fusion” of visualization of the state of execution of an exercise by a cadet/listener has been developed. Three types of simulation training exercises for CTR (control zone), TMA (terminal control area), and CTA (control area) with different complexity have been analyzed.

Information-Measuring Technologies for UAV's Application

This chapter describes two practical examples of sensors application on an unmanned aerial vehicle. The first device is a proximity sensor allowing users to measure the rotating angle of UAV's elevator. The second example discovers a measuring unit established on the UAV and processed measuring information for landing the UAV. To perform exactness control of unmanned aerial vehicles actuating mechanisms, the control system must be supplied by devices providing precision definition of values of current operation factors of those mechanisms.

Artificial Intelligence Systems in Aviation

The aim of this chapter is to research and fundamentally evaluate counterfeit shrewd frameworks to recognize for outperforming human insight in the flights and its conceivable ramifications. How artificial intelligence (AI) makes current airship framework incorporates an assortment of programmed control framework that guides the flight team in route, flight administration and enlarging the security qualities of the plane, and how building aircraft engine diagnostics ontology, air traffic management, and constraint programming (CP) is useful in ATM setting. How flight security can be enhanced through the advancement and usage of mining, utilizing its outcomes and knowledge-based engineering (KBE) approach in an all-encompassing methodology for use in airship reasonable outline, is discussed. The early recognizable proof and finding of mistakes, the study of huge information and its effect on the transportation business and enhanced transit system, the agent-based mobile airline search, and booking framework using AI are shown.