# Designing a Reliable UAV Architecture Operating in a Real Environment
## 2 Related Works
Models compliant with the MBSE methodology, widely used in systems engineering, verify individual elements of the air platform flight scenario. The MBSE approach used in the design of the air platform is described quite extensively in the literature on the subject. Examples include [4, 17]. Designing basic platform operation scenarios is not sufficient when designing a secure platform. The FHA defines the so-called emergency situations, i.e., potential failures that may occur during the flight in a given mode. Usually, for each function described in the decomposition process, potential emergency situations that may occur are indicated. The system designer's task is to design and describe the algorithms handling the occurrence of emergency situations during the flight so that the platform retains the possibility of at least a safe return in the event of one or several such events occurring in a short period. Examples of exceptional situations are the loss of a radio link with NSK, loss of a GPS signal, a potential collision of two platforms in the air, or a collision of a platform with a terrain obstacle. For many events of this type, there is literature that allows the analyst to design software to protect the platform against emergency situations. An example is the in-flight separation algorithm [9], the development of which is presented in this article. In the case of building advanced unmanned platforms, functions related to the implementation of missions during the flight are designed. These often require optimization tasks to be solved. The UAV uses deep learning neural networks for image recognition, algorithms for route planning, avoiding obstacles, etc. These algorithms require detailed descriptions and formal proof of correctness. Among these specific numerical algorithms are the algorithms used during the mission, for example, algorithms determining a change of the platform's course after detecting the possibility of a collision in the air, i.e., algorithms ensuring the separation between [9,18] platforms. In this article, we focus on the particular situation in flight related to the need to maintain the separation between two platforms whose flight trajectories intersect (also taking into account time). In such a situation, a deterministic algorithm should be designed to ensure that the appropriate minimum distance between platforms is maintained. At the same time, aircraft must be equipped with systems that communicate data about their position to others. The presence of ADS-B modules on the platform is assumed, working both as emitters and receivers. These devices broadcast flight parameters (plane position, velocity, and heading) to nearby vehicles. Having minimal information on the position and velocities of nearby airplanes allows for effective and suboptimal dodge maneuver prediction. There are three main approaches used in solving the task of separating platforms in the air, described in the literature on the subject. The first approach, the most natural and efficient, is based on determining the change in the direction of the UAV flight as well as the speed and height of the UAV based on the available data using geometric methods. These methods are characterised by a high speed of determining the solution. However,they require multiple repetitions in the case of minor modifications of the flight parameters of one of the air platforms. Geometric approaches rely on the analysis of the geometric attributes of the UAV to ensure that minimum distances between the air platforms are maintained. This requires calculating the time to potential collision using the distance between UAVs and their speed. This article is mainly based on the geometric algorithm presented by [PERSON], et al. [9]. The method proposed by [PERSON] is tested to ensure flight safety in various situations. Different algorithm, described in [19], allows the UAV to avoid obstacles of various types (including other UAVs) in 3D.