THE METHOD OF ESTIMATION POSITIONS OF THE UAVS BY MEASURING THE DISTANCES BETWEEN ELEMENTS OF THE GROUP

Abstract

Important problems in the development of mobile robotics are the task of autonomous navigation, automatic movement control and providing a reliable communication channel. For navigation, an unmanned aerial vehicle can use its own inertial navigation system and a satellite navigation system. The purpose of this article is to develop a method for reducing errors in the operation of the inertial navigation system of UAVs caused by the presence of random and systematic errors. In this case, we consider the situation of a monotonous increase in the systematic error over time. Usually, navigation data obtained from the satellite does not contain a significant systematic error in determining the coordinates. However, the satellite signal may be lost for a time significantly longer than the period of transmission of navigation data from the satellite in normal mode. As a result, there is a problem of increasing the accuracy of the data received from the inertial navigation system. This problem is particularly relevant for group application of UAVs. When solving group control tasks, it becomes necessary to prevent vehicle collisions and possible collisions already at the stage of traffic planning. In addition, to solve a number of group tasks, such as monitoring the terrain, conducting rescue operations, searching for objects in a given area, and joint cargo transportation, individual objects of the group must move smoothly in space with great accuracy. This imposes more stringent restrictions on the accuracy of the inertial navigation systems processing and the frequency of information exchange. In this paper, we propose a method that allows, based on data obtained from local systems that measure the mutual distances between objects in a group. This information allows correct the estimates of their own coordinates in such a way as to reduce the standard deviation of the corrected set of points from the true positions of objects at a given time. The method also reduces the maximum value of the corresponding deviation in comparison with the original set of estimates obtained from the navigation data of the INS. The method is demonstrated by the example of increasing the accuracy of determining global coordinates in a group of UAVs.