• Journal of Positioning, Navigation, and Timing
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• v.12 no.4
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• pp.343-348
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• 2023

The ionosphere acts as the largest error source in the Global Navigation Satellite System (GNSS) signal transmission. Ionospheric total electron content (TEC) is also easily affected by changes in the space environment, such as solar activity and geomagnetic storms. In this study, we analyze changes in the regional ionosphere using the Qusai-Zenith Satellite System (QZSS), a regional satellite navigation system. Observations from 9 GNSS stations in South Korea are used for estimating the QZSS TEC. In addition, the performance of QZSS TEC is analyzed with observations from day of year (DOY) 199 to 206, 2023. To verify the performance of our results, we compare the estimated QZSS TEC and CODE Global Ionosphere Map (GIM) at the same location. Our results are in good agreement with the GIM product provided by the CODE over this period, with an averaged difference of approximately 0.1 TECU and a root mean square (RMS) value of 2.89 TECU.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.1
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• pp.1-8
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• 2017

In this study, to design a multi-GNSS receiver using single RF front-end, the receiving performances for various frequency plans were evaluated. For the fair evaluation and comparison of different frequency plans, the same signal needs to be received at the same time. For this purpose, two synchronized RF front-ends were configured using USRP X310, and PC-based software was implemented so that the quality of the digital IF signal received at each front-end could be evaluated. The software consisted of USRP control, signal reception, signal acquisition, signal tracking, and C/N0 estimation function. Using the implemented software and USRP-based hardware, the signal receiving performances for various frequency plans, such as the signal attenuation status, overlapping of different systems, and the use of imaginary or real signal, were evaluated based on the C/N0 value. The results of the receiving performance measurement for the various frequency plans suggested in this study would be useful reference data for the design of a multi-GNSS receiver in the future.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.51-58
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• 2023

Geofencing supports unmanned aerial vehicle (UAV) operation by defining stay-in and stay-out regions. National Aeronautics and Space Administration (NASA) has developed a prototype of the geofencing function, SAFEGUARD, which prevents stayout region violation by utilizing position estimates. Thus, SAFEGUARD depends on navigation system performance, and the safety risk associated with the navigation system uncertainty should be considered. This study presents a methodology to compute the safety risk assessment-based along-track position error bound under nominal and Global Navigation Satellite Systems (GNSS) failure conditions. A Kalman filter system using pseudorange measurements as well as pseudorange rate measurements is considered for determining the position uncertainty induced by velocity uncertainty. The worst case pseudorange and pseudorange rate fault-based position error bound under the GNSS failure condition are derived by applying a Receiver Autonomous Integrity Monitor (RAIM). Position error bound simulations are also conducted for different GNSS fault hypotheses and constellation conditions with a GNSS/INS integrated navigation system. The results show that the proposed along-track position error bounds depend on satellite geometries caused by UAV attitude change and are reduced to about 40% of those of the single constellation case when using the dual constellation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.1
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• pp.23-28
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• 2021

Data analysis research using deep learning has recently been studied in various field. In this paper, we conduct a GNSS (Global Navigation Satellite System)-based meteorological study applying deep learning by estimating the ZWD (Zenith tropospheric Wet Delay) through MLP (Multi-Layer Perceptron) and LSTM (Long Short-Term Memory) models. Deep learning models were trained with meteorological data and ZWD which is estimated using zenith tropospheric total delay and dry delay. We apply meteorological data not used for learning to the learned model to estimate ZWD with centimeter-level RMSE (Root Mean Square Error) in both models. It is necessary to analyze the GNSS data from coastal areas together and increase time resolution in order to estimate ZWD in various situations.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.4
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• pp.287-295
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• 2022

The GNSS coordinate time series is used as important data for geophysical analysis such as terrestrial reference frame establishment, crustal deformation, Earth orientation parameter estimation, etc. However, various factors may cause discontinuity in the coordinate time series, which may lead to errors in the interpretation. In this paper, we describe the discontinuity in the coordinate time series due to the equipment replacement for domestic GNSS stations and discuss the change in movement magnitude and velocity vector difference in each direction before and after discontinuity correction. To do this, we used three years (2017-2019) of data from 40 GNSS stations. The average magnitude of the velocity vector in the north-south, east-west, and vertical directions before correction is -12.9±1.5, 28.0±1.9, and 4.2±7.6 mm/yr, respectively. After correction, the average moving speed in each direction was -13.0±1.0, 28.2±0.8, and 0.7±2.1 mm/yr, respectively. The average magnitudes of the horizontal GNSS velocity vectors before and after discontinuous correction was similar, but the deviation in movement size of stations decreased after correction. After equipment replacement, the change in the vertical movement occurred more than the horizontal movement variation. Moreover, the change in the magnitude of movement in each direction may also cause a change in the velocity vector, which may lead to errors in geophysical analysis.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.545-554
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• 2023

In modern industry, the Global Navigation Satellite System(GNSS) is utilized in various fields, where PNT information (P: Positioning, N: Navigation, T: Timing) is always provided and the accurate location estimation based on PNT information is required. In particular, in order to prevent the infection and the spread of the COVID-19 pandemic situation that began in 2019, the precise GNSS technology and various supporting techniques have been used, and, with active quarantine and efforts for the infection spread restrain around the world, we are facing the transition to an endemic situation. In fields of disease and E-health, the location information of users is absolutely necessary to track and monitor infectionous diseases and provide remote medical services, and GNSS plays a leading role in providing the accurate location information. This paper presents investigation results on the up-to-date research trends in which GNSS technologies are employed in the field of disease and E-health, and analyzes the results.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.391-399
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• 2012

Multipath remains a dominant source of ranging errors in GNSS (Global Navigation Satellite System). And it is generally considered undesirable in the context of GNSS, since the reception of multipath can make significant distortion to the shape of the correlation function. In this paper, therefore, the model of the distorted shape of the correlation function is formulated and a MBME (Model-Based Multipath Estimation) technique for GPS L1/L5 receivers is proposed in order to estimate the parameters of the indirect signal such as the amplitude and the delay. The MBME technique does not require the any hardware modifications and it can estimate the parameters for both the short and long-delay multipath. Especially, it would be the very effective technique for the short-delay multipath if the L5 signal is available. Finally, the feasibility of the proposed technique has been confirmed by simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2252-2260
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• 2015

In this paper, we propose a vehicular cooperative navigation system using GNSS, vision sensor and radar sensor that are frequently used in mass-produced cars. The proposed cooperative vehicular navigation system is a variant of the Hybrid-Sum Product Algorithm over Wireless Network (H-SPAWN), where we use vision and radar sensors instead of radio ranging(i.e.,UWB). The performance is compared and analyzed with respect to the sensors, especially the position estimation error decreased about fifty percent when using radar compared to vision and radio ranging. In conclusion, the proposed system with these popular sensors can improve position accuracy compared to conventional cooperative navigation system(i.e.,H-SPAWN) and decrease implementation costs.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.3
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• pp.179-187
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• 2021

To estimate the location of the train, we consider an integrated navigation system that combines Inertial Navigation System (INS) and Global Navigation Satellite System (GNSS). This system provides accurate navigation results in open sky by combining only the advantages of both systems. However, since measurement update cannot be performed in GNSS signal blocked areas such as tunnels, mountain, and urban areas, pure INS is used. The error of navigation information increases in this area. In order to reduce this problem, the train's Non-Holonomic Constraints (NHC) information can be used. Therefore, we deal with the INS/GNSS/NHC integrated navigation system in this paper. However, in the process of installing the navigation system on the train, a Mounting Misalignment Error of the IMU (MMEI) inevitably occurs. In this case, if the NHC is used without correcting the error, the navigation error becomes even larger. To solve this problem, a method of easily estimating the MMEI without an external device is introduced. The navigation filter is designed using the Extended Kalman Filter (EKF) by considering the MMEI. It is assumed that there is no vertical misalignment error, so only the horizontal misalignment error is considered. The performance of the integrated navigation system according to the presence or absence of the MMEI and the estimation performance of the MMEI according to the method of using NHC information are analyzed based on simulation. As a result, it is confirmed that the MMEI is accurately estimated by using the NHC information together with the GNSS information, and the performance and reliability of the integrated navigation system are improved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.11-21
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• 2020

This paper deals with the impact of a GNSS (Global Navigation Satellite System) antenna radome on the PCV (Phase Center Variations) and the estimated kinematic coordinates. For the Trimble and Leica antennas, specially set up CORS (Continuously Operation Reference Stations) in Korea, the PCC (Phase Center Corrections) were calculated and compared for NONE, SCIS, SCIT, and TZGD radome from the PCV model published by the IGS (International GNSS Services). The results revealed that the PCC differences compared to the NONE were limited to about 1mm in the horizontal component while those of the vertical direction ranged from a few millimeters to a maximum of 7mm. Among the radomes of which PCV were compared, the SCIT had the most significant influence on the vertical component, and its GPS (Global Positioning System) L2 and L2 PCC (Phase Center Corrections) had opposite direction. As a result of comparing the kinematic coordinates estimated by the baseline processing of 7 CORSs with an application of the PCV models of the various radomes, the SCIS which was actually installed at CORS in Korea showed 3.4mm bias, the most substantial impact on the ellipsoidal height estimation whereas the SCIT model resulted in relatively small biases.