arXiv subjects

Pyo-Woong Son

Publications and source records attributed to Pyo-Woong Son.

15 recordsLinked to original sources

arXiv2026

AIS-Based Maritime GNSS RFI Monitoring With Multi-Vessel Coherence and Communication-Integrity Artifact Mitigation

Global Navigation Satellite System (GNSS) radio-frequency interference (RFI), including spoofing and jamming, threatens maritime positioning, navigation, and timing. Automatic Identification System (AIS) reports provide GNSS-derived vessel positions, offering an opportunistic wide-area monitoring source; however, raw AIS streams contain communication-integrity artifacts, such as duplicated ship identifiers and stale-data retransmissions, that can mimic trajectory distortion or reporting outages, and isolated single-vessel anomalies cannot be unambiguously attributed to GNSS interference. This paper proposes an AIS-based framework that mitigates communication-integrity artifacts, generates kinematic-consistency and transmission-continuity anomaly cues, and groups retained cues into multi-vessel events using spatiotemporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN). Applied to approximately 966 million AIS messages from Korean coastal waters, the framework retained 48 spoofing-consistent distortion events and 98 jamming-consistent reporting-outage events. These results suggest that AIS can serve as a complementary source for maritime GNSS RFI monitoring.

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arXiv2026

Track-Consistency-Based GNSS RFI Monitoring Using Crowdsourced ADS-B Sensor Networks

Growing reports of global navigation satellite system (GNSS) radio-frequency interference (RFI) highlight the need for scalable wide-area sensing for situational awareness. Crowdsourced Automatic Dependent Surveillance-Broadcast (ADS-B) receiver networks form a large-scale opportunistic sensor network for GNSS RFI monitoring, but ADS-B quality indicators may remain high during abnormal reported-position behavior, and heterogeneous receiver timestamping can produce apparent speed spikes. This letter proposes a three-stage framework that screens position-jump candidates, verifies local track consistency to suppress timing artifacts, and groups confirmed anomalies into traffic-adaptive multi-aircraft events. Using 605 million 1090-MHz ADS-B reports over Northeast Asia from December 2025 to February 2026, the framework identified 166 event clusters within the validity window of Notice to Airmen (NOTAM) RKRR Z1401/25 and none in the pre-NOTAM period. More than 99% of confirmed anomalies remained in high quality-indicator regimes, suggesting that track-consistency verification provides a complementary sensing criterion for GNSS RFI monitoring.

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arXiv2026

Wide-Area GNSS Interference Monitoring with CYGNSS GNSS-R Delay-Doppler Noise Floor Observations

Global Navigation Satellite System (GNSS) interference increasingly threatens positioning, navigation, and timing services and requires monitoring over areas beyond dense ground networks. Low Earth orbit satellites provide complementary regional coverage, and previous studies have shown that terrestrial radio-frequency interference (RFI) produces measurable anomalies in spaceborne GNSS and GNSS-reflectometry observations. The Cyclone Global Navigation Satellite System (CYGNSS) has been used to map and characterize interference, but existing approaches generally depend on long-term data accumulation, full Delay-Doppler Map (DDM) processing, or special raw intermediate-frequency acquisitions and lack epoch-level validation against independent data. This paper presents a lightweight detector using four channel-wise DDM noise-floor values routinely distributed in CYGNSS Level-1 products. Because the channels observe different reflected signals through two nadir antennas, interference-related elevations may be strongly asymmetric. The detector uses the channel maximum to preserve these responses and applies temporal-persistence or multi-satellite-concurrence screening to reject isolated anomalies. Evaluation at the White Sands Missile Range used an independent reference formed from Federal Aviation Administration Notices to Air Missions and concurrent Automatic Dependent Surveillance-Broadcast navigation-integrity degradation. Relative to the single-epoch mean baseline, the proposed detector increased the probability of detection by 0.063 at the same observed false-alarm rate, with a 95% confidence interval of [0.034, 0.094]. In the Middle East, it also detected both vertical-stripe and atypical elevated-background DDM structures. These results demonstrate lightweight epoch-level monitoring of wide-area or temporally sustained GNSS interference using routine Level-1 products.

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arXiv2025

Performance Evaluation of eLoran Spatial ASF Corrections Based on Measured ASF Map

This paper analyzes the effectiveness of spatial ASF correction methods in the Korean eLoran system using measured ASF maps. Three correction scenarios were evaluated under identical simulation settings: no correction (S0), local correction using true ASF values (S1), and wide-area correction using a single reference station value (S2). Simulation results show that S1 consistently achieved the lowest positioning errors, while S0 exhibited the largest errors with extensive high-error regions. S2 provided limited improvements near the reference station but degraded with increasing distance and ASF spatial gradients. The findings highlight that local ASF correction significantly improves eLoran positioning performance, whereas wide-area correction has only localized benefits.

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arXiv2025

Correlation Analysis Between MF R-Mode Temporal ASF and Meteorological Factors

As the vulnerabilities of global navigation satellite systems (GNSS) have become more widely recognized, the need for complementary navigation systems has grown. Medium frequency ranging mode (MF R-Mode) has gained attention as an effective backup system during GNSS outages, owing to its strong signal strength and cost-effective scalability. However, to achieve accurate positioning, MF R-Mode requires correction for the additional secondary factor (ASF), a propagation delay affected by terrain. The temporal variation of ASF, known as temporal ASF, is typically corrected using reference stations; however, the effectiveness of this method decreases with distance from the reference station. In this study, we analyzed the correlation between temporal ASF and meteorological factors to evaluate the feasibility of predicting temporal ASF based on meteorological factors. Among these factors, temperature and humidity showed significant correlations with temporal ASF, suggesting their potential utility in ASF correction.

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arXiv2025

Enhancing eLoran Timing Accuracy via Machine Learning with Meteorological and Terrain Data

The vulnerabilities of global navigation satellite systems (GNSS) to signal interference have increased the demand for complementary positioning, navigation, and timing (PNT) systems. To address this, South Korea has decided to deploy an enhanced long-range navigation (eLoran) system as a complementary PNT solution. Similar to GNSS, eLoran provides highly accurate timing information, which is essential for applications such as telecommunications, financial systems, and power distribution. However, the primary sources of error for GNSS and eLoran differ. For eLoran, the main source of error is signal propagation delay over land, known as the additional secondary factor (ASF). This delay, influenced by ground conductivity and weather conditions along the signal path, is challenging to predict and mitigate. In this paper, we measure the time difference (TD) between GPS and eLoran using a time interval counter and analyze the correlations between eLoran/GPS TD and eleven meteorological factors. Accurate estimation of eLoran/GPS TD could enable eLoran to achieve timing accuracy comparable to that of GPS. We propose two estimation models for eLoran/GPS TD and compare their performance with existing TD estimation methods. The proposed WLR-AGRNN model captures the linear relationships between meteorological factors and eLoran/GPS TD using weighted linear regression (WLR) and models nonlinear relationships between outputs from expert networks through an anisotropic general regression neural network (AGRNN). The model incorporates terrain elevation to appropriately weight meteorological data, as elevation influences signal propagation delay. Experimental results based on four months of data demonstrate that the WLR-AGRNN model outperforms other models, highlighting its effectiveness in improving eLoran/GPS TD estimation accuracy.

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arXiv2024

Accuracy Simulation of MF R-Mode Systems Using TOA Variance

To ensure consistent navigation services despite GNSS signal disruptions, Korea is developing the R-Mode system. This study focuses on enhancing the simulation accuracy of the MF R-Mode system's performance by integrating data from the Eocheong transmitter with existing data from the Palmi and Chungju transmitters. Additional measurements from these three transmitters were gathered using the DARBS receiver to model the Time-of-Arrival(TOA) variance. Analysis of this data facilitated the calculation of new constants and transmitter specific jitter values, which were then used to determine coverage areas based on the updated parameters.

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arXiv2024

Ground Truth Generation Algorithm for Medium-Frequency R-Mode Skywave Detection

With the advancement of transportation vehicles, the importance and utility of navigation systems providing positioning, navigation, and timing (PNT) information have been increasing. Global navigation satellite systems (GNSS) are widely used navigation systems, but they are vulnerable to radio frequency interference (RFI), resulting in disruptions of satellite navigation signals. Recognizing this limitation, extensive research is being conducted on alternative navigation systems. In the maritime industry, ongoing research focuses on a groundbased integrated navigation system called R-Mode. R-Mode utilizes medium frequency (MF) differential GNSS (DGNSS) and very high-frequency data exchange system (VDES) signals as ranging signals for positioning and incorporates the existing ground-based navigation system known as enhanced long-range navigation (eLoran). However, MF R-Mode, which uses MF DGNSS signals for positioning, exhibits significant performance differences between daytime and nighttime due to skywave interference caused by signals reflecting off the ionosphere. In this study, we propose a skywave ground truth generation algorithm that is crucial for studying mitigation methods for MF R-Mode skywave interference. Furthermore, we demonstrate the proposed algorithm using field-test data.

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arXiv2022

Simulation of Medium-Frequency R-Mode Signal Strength

Assuming failure in the global navigation satellite systems due to radio frequency interference and ionospheric anomaly, an R-Mode system, a terrestrial integrated navigation system, is being actively studied for domestic deployment in South Korea. In this study, parameters for an approximate calculation of the received signal strength were obtained and applied to develop a performance simulation tool for a medium-frequency R-Mode system. As a case study, the signal strength from the Yeongju transmitter was simulated using the proposed parameters.

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arXiv2022

Preliminary Analysis of Skywave Effects on MF DGNSS R-Mode Signals During Daytime and Nighttime

Accurate positioning, navigation, and timing (PNT) performance are prerequisites for several technologies today. In a marine environment, it is difficult to visually identify one's position accurately, leading to safety concerns. Currently, PNT information is provided mainly from Global Navigation Satellite Systems (GNSS); however, it is vulnerable to radio frequency interference, spoofing, and ionospheric anomaly. Therefore, research on a backup system is needed. Ranging Mode (R-Mode), a terrestrial integrated navigation system, is being investigated for use in a marine environment. R-Mode is a positioning technology that integrates terrestrial signals of opportunity such as medium frequency (MF) differential GNSS (DGNSS), very high frequency (VHF) automatic identification system (AIS), and enhanced long-range navigation (eLoran) signals. Previous studies in Europe show that signals in the MF band differ greatly in accuracy between daytime and nighttime. This difference is primarily caused by skywave. In this study, the MF DGNSS R-Mode signal transmitted from Chungju, Korea was received in Daesan and Daejeon, Korea. The skywave effect during daytime and nighttime was compared and investigated. In addition, the continuous wave intensity of the R-Mode signal was increased during the nighttime to compare its effect on the measurement accuracy.

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arXiv2021

First Demonstration of the Korean eLoran Accuracy in a Narrow Waterway Using Improved ASF Maps

The vulnerabilities of global navigation satellite systems (GNSSs) to radio frequency jamming and spoofing have attracted significant research attention. In particular, the large-scale jamming incidents that occurred in South Korea substantiate the practical importance of implementing a complementary navigation system. This letter briefly summarizes the efforts of South Korea to deploy an enhanced long-range navigation (eLoran) system, which is a terrestrial low-frequency radio navigation system that can complement GNSSs. After four years of research and development, the Korean eLoran testbed system has been recently deployed and is operational since June 1, 2021. Although its initial performance at sea is satisfactory, navigation through a narrow waterway is still challenging because a complete survey of the additional secondary factor (ASF), which is the largest source of error for eLoran, is practically difficult in a narrow waterway. This letter proposes an alternative way to survey the ASF in a narrow waterway and improve the ASF map generation methods. Moreover, the performance of the proposed approach was validated experimentally.

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arXiv2021

Development of an R-Mode Simulator Using MF DGNSS Signals

With the development of positioning, navigation, and timing (PNT) information-based industries, PNT information is becoming increasingly important. Therefore, various navigation studies have been actively conducted to back up global positioning system (GPS) in scenarios in which it is disabled. Ranging using signals of opportunity (SoOP) has the advantage of infrastructure already being in place. Among them, the ranging mode (R-Mode) is a technology that uses available SoOPs such as a medium frequency (MF) differential global navigation satellite System (DGNSS) signal that has recently been recognized for its potential for navigation and is currently under research. In this study, we developed a signal simulator that considers the characteristics of MF DGNSS signals and skywaves used in R-Mode.

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arXiv2021

Enhanced Accuracy Simulator for a Future Korean Nationwide eLoran System

The Global Positioning System (GPS) has become the most widely used positioning, navigation, and timing system. However, the vulnerability of GPS to radio frequency interference has attracted significant attention. After experiencing several incidents of intentional high-power GPS jamming trials by North Korea, South Korea decided to deploy the enhanced long-range navigation (eLoran) system, which is a high-power terrestrial radio-navigation system that can complement GPS. As the first phase of the South Korean eLoran program, an eLoran testbed system was recently developed and declared operational on June 1, 2021. Once its operational performance is determined to be satisfactory, South Korea plans to move to the second phase of the program, which is a nationwide eLoran system. For the optimal deployment of additional eLoran transmitters in a nationwide system, it is necessary to properly simulate the expected positioning accuracy of the said future system. In this study, we propose enhanced eLoran accuracy simulation methods based on a land cover map and transmitter jitter estimation. Using actual measurements over the country, the simulation accuracy of the proposed methods was confirmed to be approximately 10%-91% better than that of the existing Loran (i.e., Loran-C and eLoran) positioning accuracy simulators depending on the test locations.

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arXiv2020

Effect of Outlier Removal from Temporal ASF Corrections on Multichain Loran Positioning Accuracy

The widely used global navigation satellite systems (GNSSs) are vulnerable to radio frequency interference (RFI). Long-range navigation (Loran), a terrestrial navigation system, can compensate for this weakness; however, it suffers from low positioning accuracy, and studies are under way to improve its positioning performance. One such study has proposed the multichain Loran positioning method that uses the signals of transmitting stations belonging to different chains. Although the multichain Loran positioning performance is superior to the performance of conventional methods, the additional secondary factor (ASF) can still degrade its positioning accuracy. To mitigate the effects of temporal ASF, which is one of the ASF components, it is necessary to obtain temporal correction data from a nearby reference station at a known location. In this study, an experiment is performed to verify the effect of removing the outliers in the temporal correction data on the multichain Loran positioning accuracy.

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arXiv2020

Development of Record and Management Software for GPS/Loran Measurements

In this paper, a software implementation that records Global Positioning System (GPS) and long-range navigation (Loran) measurement data output from an integrated GPS/Loran receiver and organizes them based on time is proposed. The purpose of the developed software is to collect measurements from multiple Loran transmitter chains for performance analysis of navigation methods using Loran, and to organize the data based on time to make it easy to use them. In addition, GPS measurements are also collected and managed as ground truth data for performance analysis. The implemented software consists of three modules: recording, classification, and conversion. The recording module records raw text data streamed from the receiver, and the classification module classifies the recorded text data according to the message format. The conversion module parses the classified text data, sorts GPS and Loran measurements based on timestamp, and outputs them according to the software platform of the user to analyze the measurements. Each module of the software runs automatically without user intervention. The functionality of the implemented software was verified using GPS and Loran measurements collected over 24 h from an actual integrated GPS/Loran receiver.

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