The use of UAV is widespread both in industrial or amateur projects and adapted for many others missions over long distances. Usually, a large number of factors affect the development of a system or algorithm, and also complicates the processes of data acquisition, transmission and calculation, especially when there is no external navigation communication. This article presents an algorithm for identifying an object by a color mask, establishing the real distance and finding its spatial coordinates based on data obtained from the camera and onboard sensors of deviation angles. A description of the necessary components and functions for creating an algorithm for establishing the spatial X and Y coordinates of a detected object is also presented. Software architecture is designed in such a way that each block is autonomous and easily integrated. Taking into account the functional structure of the avionics equipment, the optimal approach to implementing the method was selected. The calculations are based on trigonometric equations and information about the state of vehicle. In addition, the algorithm was tested on a small quadcopter model with process optimization, which improved its autonomy and increased the accuracy of real-time calculations.