Autonomous control systems development of aerial vehicles is one of the promising directions of modern unmanned aviation. One of the complicated factor of Unmanned aerial vehicles development is the need to test the system in various environmental conditions, such as insufficient or excessive lighting, increased cloud cover, and other factors that impact the performance of control algorithms. Therefore, the development of tools for flight test simulation is a crucial scientific task to significantly enhance the efficiency of guidance system development. This paper describes a system based on Unreal Engine and the OpenCV library, which allows for the simulation of field tests for UAV guidance algorithms targeting a specified objective. This process involves synthesizing information about the virtual environment (video data from a virtual onboard camera and virtual sensors) and providing it as input signals to the control algorithm. Based on the algorithm’s performance, reports are generated to evaluate its effectiveness, enabling further optimization and the elimination of deficiencies.