The paper proposes a technology for automated video-based observation (VBO) of a drogue-sensor in the problem of aerial refueling. The technology is based on the use of a passive optoelectronic system and incorporates the logic of automated refueling observation of a refueling process using algorithms for the automatic detection and tracking of a drogue-sensor, a methodical apparatus for suboptimal linear filtering of the observed process under the conditions of spatial and temporary non-stationarity of the refueling process, algorithms for automatic correlation detection and tracking of a drogue-sensor using suboptimal filtering. An analysis of the design of experimental foreign systems for autonomous aerial refueling is carried out. The choice of the algorithm for the functioning of the synthetic vision system is substantiated. It is established that the main observation procedures: detection, capture for tracking and determination of the current drogue coordinates with a given rate and quality should be performed automatically, the pilot-operator takes part in the operation of the synthetic vision system in case of capture errors or mistracking. The statement of the problem for automated VBO of a drogue-sensor is formulated. A structural-logical diagram of the automated observation process, including the detection and tracking of a drogue, as well as decision-making by the pilot in various situations, is proposed. A modeling complex for a synthetic vision system operation is presented. The results of experimental studies of the synthetic vision system efficiency are presented. Based on the developed technology and the results of evaluating the effectiveness of automated observation algorithms, a strategy for performing autonomous refueling in conditions of various turbulence is proposed, while, during weak turbulence, a successful engagement is provided by tracking the center of drogue oscillations, in turn, under conditions of severe turbulence, a successful engagement can be provided by tracking a drogue controlled according to the synthetic vision system data.