Abstract

In this article the feasibility of using an improved pseudolongdimensional method to determine the coordinates of terrestrial targets using small-scale unmanned aerial vehicles (UAVs), which is used to identify the coordinates of an object on the ground in real-time without involving of powerful computable technique, is justified.The analysis of existing methods for determining the coordinates of terrestrial objects using unmanned aerial vehicles is carried out and an algorithm for determining them based on an improved pseudolongdimensional method using small- scale unmanned aerial vehicles is proposed.The determining the coordinates of terrestrial objects using existing unmanned aerial vehicles is carried out by comparing the image, which was obtained from a located on the unmanned aerial vehicles video camera, with an electronic territory map, on which the observation takes place. The coordinates of the point on the terrain are determined after reaching of maximum coincidence of specified images. The accuracy and timing the coordinates of the point depends on the quality of the image, the number of images, the angle and other factors.An algorithm for determining the coordinates of terrestrial targets using small-scale unmanned aerial vehicles based on an improved pseudolongdimensional method was proposed based on the analysis of the unmanned aerial vehicles work to identify the coordinates of the point on the terrain. The pseudolongdimensional method is used in modern satellite navigation receivers, which is solved by using methods of "least squares", "successive approximations" and etc.The analysis of the accuracy estimation shows that the errors of the coordinate’s determination of the target by the proposed method will depend only on the accuracy of determining the current coordinates of small- scale the unmanned aerial vehicles at the points, where the picture was taken, and the accuracy of the measuring of the corresponding values of the range to the target. To determine the coordinates of a target there is no need for large amounts of memory and powerful computing resources.

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