Detecting obstacles during the flight and avoiding them is desirable in the case of unmanned aerial vehicles intended for observation of a residential area, refers especially to lightweight micro-aviation vehicles of multi-rotor type, and is also a serious problem because their load capacity is limited, therefore only electronic sensors can be connected to the object. Usually the sensors built into the system are either based on a type vision (monocular or stereo camera) or on a laser camera. However, each of the sensors has its advantages and disadvantages, which is why the article presents the concept of a system for collecting data characterizing the flight of a UAV object and including them in the object identification process. The main purpose of this work is to perform selected studies (analysis, mathematical model, simulations) in the field of identification of small unmanned flying objects. A dynamic model describing UAV motion was developed, which took into account flight parameters using various identification methods. The structure of this work is contained in four chapters, in which, among others, the second chapter deals with the review of existing identification systems for small UAV objects, based on an analysis of the literature on the subject of research. The third chapter covers the issues related to aerodynamics and mechanics of small UAV objects and concerns linear longitudinal equations of UAVs based on Newton's second law. This chapter also describes the algorithm used for dynamic description along with incorrect filtering of "on-line" learning patterns and characterizes the least squares recursive method used for the simulation. Based on the analysis, mathematical models created, simulations performed and the results obtained based on them, practical conclusions presented in the final part of the article were formulated.