IOD 변화 시점에서 다항식 모델을 사용한 IGS RTS 보정정보 예측 = Prediction of the IGS RTS Correction using Polynomial Model at IOD Changes

국문 초록 (Abstract)

IGS에서 제공하는 RTS (real-time service) 정보는 인터넷으로 GNSS 궤도 및 시계에 대한 실시간 보정값을 제공하므로 실시간 정밀 위치추정에 많이 사용된다. 하지만 인터넷 환경이 불안정한 경우 RTS 신호가 단절될 수 있는데, 주로 다항식을 이용하여 손실된 신호예측을 수행한다. GNSS 항법메시지 IOD (issue of data)가 변화하는 구간에서는 RTS 보정정보도 급격히 변화하여 불연 속성이 증가하고, 신호단절이 발생할 경우 예측이 어려운 문제가 발생한다. 본 연구에서는 IOD 변화에 의한 항법메시지 궤도 차이를 적용하여 연속적인 RTS 보정정보를 생성하는 방법을 제안하였다. 이를 이용하면 RTS 신호손실이 IOD 변화 직후 발생할 경우 예측 성능을 높일 수 있다. RTS 예측성능을 높이기 위한 최적화 연구를 수행한 뒤, 예측된 RTS 궤도정보를 정밀위치결정(PPP; precise point positioning)에 적용하였다. 기존 방법에 비해 위치오차가 상당히 감소하였으며, 신호손실 구간이 길어질수록 위치오차가 급증하는 경향도 감소하였다.

다국어 초록 (Multilingual Abstract)

Real-time service (RTS) provided by IGS provides correction for GNSS orbit and clock via internet, so it is widely used in fields that require real-time precise positioning. However, the RTS signal may be lost due to an unstable Internet environment. When signal disconnection occurs, signal prediction can be performed using polynomial models. However, the RTS changes rapidly after the GNSS navigation message issue of data (IOD) changes, so it is difficult to predict when signal loss occurs at that point. In this study, we proposed an algorithm to generate continuous RTS correction information by applying the difference in navigation trajectory according to IOD change. The use of this algorithm can improve the accuracy of RTS prediction at IOD changes. After performing optimization studies to improve RTS prediction performance, the predicted RTS trajectory information was applied to precision positioning (PPP). Compared to the conventional method, the position error is significantly reduced, and the error increase along with the signal loss interval increase is reduced.

참고문헌 (Reference)

1 International GNSS Service, "Real-time Service Prod"

2 RTCM, "RTCM Standard 10403.1 differential GNSS services – version 3. RTCM Special Committee no. 104"

3 "RTCM SC-104 SSR Working Group and IGS Real-Time Working Group, IGS State Space Representation (SSR) Format Version 1.00"

4 M. G. Kim, "Predicting IGS RTS corrections using ARMA neural networks" 2015 (2015): 1-11, 2015

5 M. Elsobeiey, "Performance of real-time precise point positioning using IGS real-time service" 20 (20): 565-571, 2016

6 X. Cao, "Performance assessment of uncombined precise point positioning using Multi-GNSS real-time streams : Computational efficiency and RTS interruption" 62 (62): 3133-3147, 2018

7 A. El-Mowafy, "Maintaining real-time precise point positioning during outages of orbit and clock corrections" 21 (21): 937-947, 2017

8 Y. Lv, "Improved Short-Term Clock Prediction Method for Real-Time Positioning" 17 (17): 1308-, 2017

9 T. Hadas, "IGS RTS precise orbits and clocks verification and quality degradation over time" 19 (19): 93-105, 2015

10 M. G. Kim, "GA-ARMA model for predicting IGS RTS corrections" 2017 (2017): 1-7, 2017

11 Z. Nie, "An approach to GPS clock prediction for real-time PPP during outages of RTS stream" 22 (22): 2017

12 M. G. Kim, "An analysis of the IGS RTS correction changes after IOD changes" 47-48, 2020

13 M. G. Kim, "A performance analysis of the IGS real-time service" 225-228, 2016

14 S. Bhattarai, "A performance analysis of the IGS predictions of the GPS satellite clocks" 2014

15 김민규, "A Short-Term Prediction Method of the IGS RTS Clock Correction by using LSTM Network" 사단법인 항법시스템학회 8 (8): 209-214, 2019