ETE Model and High Precision Positioning for Autonomous Flight in 5G

Abstract

In a 5G environment, it is possible to provide various services that have not been experienced before based on high-speed infrastructure. In particular, high-precision positioning data with a very low error range is essential information for intelligent convergence technologies that provide high-quality services. For example, high-precision positioning data with a minimized error range will be essential for autonomous flight drones to fly stably in the city. A GPS is basically used for autonomous flight, and in general, factors that reduce the accuracy of GPS location measurement can be divided into three. First, there are errors caused by structural factors such as satellite time errors, satellite position errors, refraction and noise of ionized and convective layers, and multipaths. Second, there is a geometric error according to the satellite's location situation, and finally, there is Selective Availability (SA), which is the cause of the largest error. The errors that these factors produce vary greatly depending on the time and place. Various studies have been conducted to increase the accuracy of GPS positioning, developing from a calibrated satellite navigation system (DGPS) with a few meter-level of position accuracy to a carrier calibrated satellite navigation system (CDGPS) with a few centimeter-level of position accuracy. However, in order to expect a few centimeters of location accuracy, the amount of computation is higher than that of the location calculation using the code, and the integrity of the system is reduced, so the areas used are limited to narrow areas. Therefore, this paper proposes an End to End (ETE) model, an SDN network structure that can overcome the shortcomings of a 5G high-band frequencies and existing SDN structures, have a close relationship with reliability and delay, and prepare for unexpected situations. In addition, system-level analysis was conducted through simulation on the relationship between the layer to which the drone should request information and the information collection cycle and RTD, which are most important in determining this layer according to the cell radius and drone speed. Furthermore, the exact location of the drone was measured through a three-sided survey using the ETE communication network model so that the drone could land at the target point where the error range was minimized. © 2022, Success Culture Press. All rights reserved.