Purpose: This paper aims to present a vision-based method for determination of the position of a fixed-wing aircraft that is approaching a runway.Design methodology/approach: The method determines the location of an aircraft based on positions of precision approach path indicator lights and approach light system with sequenced flashing lights in the image captured by an on-board camera.Findings: As the relation of the lighting systems to the touchdown area on the considered runway is known in advance, the detected lights, seen as glowing lines or highlighted areas, in the image can be mapped onto the real-world coordinates and then used to estimate the position of the aircraft. Furthermore, the colours of lights are detected and can be used as auxiliary information.Practical implications: The presented method can be considered as a potential source of flight data for autonomous approach and for augmentation of manual approach.Originality/value: In this paper, a feasibility study of this concept is presented and primarily validated.

The paper presents automatic control of an aircraft in the longitudinal channel during automatic landing. There are two crucial components of the system presented in the paper: a vision system and an automatic landing system. The vision system processes pictures of dedicated on-ground signs which appear to an on-board video camera to determine a glide path. Image processing algorithms used by the system were implemented into an embedded system and tested under laboratory conditions according to the hardware-in-the-loop method. An output from the vision system was used as one of the input signals to an automatic landing system. The major components are control algorithms based on the fuzzy logic expert system. They were created to imitate pilot actions while landing the aircraft. Both systems were connected with one another for cooperation and to control an aircraft model in a simulation environment. Selected results of tests presenting control efficiency and precision are shown in the final section of the paper.

Present-day technologies used in SHM (Structural Health Monitoring) systems in many implementations are based on wireless sensor networks (WSN). In the context of the continuous development of these systems, the costs of the elements that form the monitoring system are decreasing. In this situation, the challenge is to select the optimal number of sensors and the network architecture, depending on the wireless system’s other parameters and requirements. It is a challenging task for WSN to provide scalability to cover a large area, fault tolerance, transmission reliability, and energy efficiency when no events are detected. In this article, fundamental issues concerning wireless communication in structural health monitoring systems (SHM) in the context of non-destructive testing sensors (NDT) were presented. Wireless technology developments in several crucial areas were also presented, and these include engineering facilities such as aviation and wind turbine systems as well as bridges and associated engineering facilities.

The paper presents the concept of a component of an aircraft’s automatic flight control system, controlling the airplane when in longitudinal motion (i.e., pitch angle, sink rate, airspeed channels) during automatic landing, from a final approach until a touchdown. It is composed of two key parts: a vision system and an automatic landing system. The first part exploits dedicated image-processing algorithms to identify the number of red and white PAPI lights appearing on an onboard video camera. Its output data—information about an aircraft’s position on a vertical profile of a landing trajectory—is used as one of the crucial inputs to the automatic landing system (the second part), which uses them to control the landing. The control algorithms implemented by the automatic landing system are based on the fuzzy logic expert system and were developed to imitate the pilot’s control actions during landing an aircraft. These two parts were teamed together as a component of a laboratory rig, first as pure software algorithms only, then as real hardware modules with downloaded algorithms. In two test campaigns (software in the loop and hardware in the loop) they controlled an aircraft model in a simulation environment. Selected results, presenting both control efficiency and flight precision, are given in the final section of the paper.

In the near future, the integration of manned and unmanned aerial vehicles into the common airspace will proceed. The changes taking place mean that the safety of light aircraft, ultralight aircraft and unmanned air vehicles (UAV) will become an increasing problem. The IDAAS project (Intruder Detection And collision Avoidance System) meets the new challenges as it aims to produce technically advanced detection and collision avoidance systems for light and unmanned aerial vehicles. The work discusses selected elements of research and practical tests of the intruder detection vision system, which is part the of IDAAS project. At the outset, the current formal requirements related to the necessity of installing anticollision systems on aircraft are presented. The concept of the IDAAS system and the structure of algorithms related to image processing are also discussed. The main part of the work presents the methodology developed for the needs of dedicated flight tests, its implementation and the results obtained. The initial tests of the IDAAS system carried out on an ultralight aircraft generally indicate the possibility of the effective detection of intruders in the airspace with the use of vision methods, although they also indicated the existence of conditions in which this detection may prove difficult or even impossible.