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This paper presents a vision system that measures the position of an aircraft relative to the runway (RWY) during a landing approach. It was assumed that all the information necessary for a correct approach was based entirely on an analysis of the image of the runway and its surroundings. It was assumed that the way the algorithm works, as well as possible, should imitate the pilot's perception of the runway. Taking into account the above and the fact that the infrastructure at each airport is different, it has been decided to use artificial neural networks with a dedicated learning process for any airport, based on the simulation environments. Such an action will enable the generation of a synthetic video sequence without the need for costly and time-consuming flights. The presented solution was tested in real flight conditions on an experimental aircraft, and the selected test results are presented in this article.

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.

The paper presents a methodology enabling the detection of aircraft touchdowns based on data obtained from accelerometers attached to the structural parts of the airframe in the cockpit or passenger compartment. Precise determination of the moment and place of touchdown of the main landing gear is challenging when analysing parameters such as height, flight speed and rate of descent. During the tests of the I-31T aircraft, it turned out that vibrations of the aircraft structure caused by the contact of the front and main landing gear with the ground have a repetitive character. In particular, this applies to longitudinal acceleration. The use of continuous wavelet analysis (CWT) allowed finding unique periodic features of the landing phenomenon that distinguish it from other forms of vibration occurring in individual flight phases. Ground and flight observations of experimental aeroplane MP-02 Czajka verified the proposed method of virtual touchdown detection. The results presented in this paper justify that this method may find broader application, especially for the light aircraft class.