V.E. Dementiev - Ph. D. (Eng.), Associate Professor, Department «Telecommunications», Ulyanovsk State Technical University E-mail: vitawed@mail.ru H.A. Abdulkadhim - Post-graduate Student, Department «Telecommunications», Ulyanovsk State Technical University E-mail: hussein73@mail.ru A.G. Frenkel - Post-graduate Student, Department «Telecommunications», Ulyanovsk State Technical University E-mail: j.skvoll@gmail.com

Modern unmanned aerial vehicles (UAVs) have a complex on-board microprocessor-based system, involving a diverse array of sensors. To solve the UAV control is necessary to ensure the positioning of UAVs, including with respect to the surrounding objects, the construction area of electronic cards, for suspicious objects, etc. Currently, most of the decisions on automatic piloting drones by using global positioning systems GPS / GLONASS. The disadvantages of such systems include the relatively low positioning accuracy, a significant delay from the satellite signals, the inability to work indoors, lack of response to obstacles, etc. To address these and other problems in this paper, we propose to use the algorithms for digital image processing of surrounding objects, designed for solving a variety of stand-alone object management tasks. Developed algorithms require aggregation of data from sensors installed on board the UAV. Among these sensors are key satellite navigation system (SNS), inertial navigation system (INS), the height sensors. The resulting data from these devices stream is combined with the results of the processing of the video stream with onboard cameras and spatial range finders. Consider video sequences processing procedure recorded on-board recording devices. This focuses on the temporal sequence of images from the camera aimed straight down, and according to the front of the infrared range finder. Note that the sequence of digital images from the bottom of the camera allows you not only to evaluate the path of the UAV, but also to create an electronic map of the area. At the same time, and the task of building the UAV trajectory and the task of building maps of the underlying surface on the video sequence can be viewed as the problem of estimating spatial geometric deformation (or binding) of adjacent frames with the accumulation of estimates. In this paper, this problem is solved by the use of adaptive recurrent pseudo-gradient procedures. When building a community card each subsequent frame is «glued» to the first inter-frame based on the evaluation of deformations. To optimize the evaluation procedures in order to increase the efficiency of the algorithm, as well as improve the reliability of the system used by the information coming from the inertial UAV systems. As such information may be used angles of the axes system, as well as the current altitude. This data is offered to use in the model image deformation that reduces the number of estimated parameters. By a similar scheme implemented by positioning the UAV according to the front of the spatial range finder. The results of the analysis of the accuracy of the algorithms depending on the length and characteristics of the route, as well as the number and location of the observed objects. It was found that at a sufficiently high frequency of receiving frames in the video sequence analysis of the resulting estimates inter-frame geometric deformations allows you to set the parameters of the character and move to within tens of centimeters. The quantitative characteristics of the effectiveness of the algorithms allow us to recommend them for use in the real world UAV control problems.

 

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