• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.116-125
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• 2020

Incalculable damage will be incurred if the national infrastructure that provides services using GNSS signals is affected by jamming signals. To prevent this, a nationwide GNSS jamming monitoring network is necessary to detect the occurrence of a jamming signal, determine the type, and properly localize the jammer position. In this paper, 2-D images for live GNSS signals were generated to verify the environment of the jamming signals through the presence and type of GNSS jamming signals at K-City, which are the test beds for self-driving vehicles, and Incheon International Airport. The analysis was also conducted to detect the occurrence of the jamming signals, determine the type, and measure the jamming signal strength. As a result, a CWI type of jamming signal was detected in L2 band at K-City and in L5 band at Incheon International Airport.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.58-65
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• 2017

Global navigation satellite system (GNSS) has a weakness of signal integrity caused by broadcasting type data transmitting direct to user from navigation satellite. Loss of GNSS signal integrity can make a catastrophic event in the operation of unmanned aerial system (UAS) because position decision is only depended on GNSS. So it is required to apply alternative method to reduce a risk and to guarantee a GNSS signal integrity for UAS operation. This paper addressed the reason of loosing GNSS signal integrity, the effectiveness of signal jamming/spoofing and GNSS application trend for UAS. Also suggested the flight safety enhancing method in case of GNSS signal jamming for UAS as technical and political approaches.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.24 no.4
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• pp.1-5
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• 2016

As a dependency on Global Navigation Satellite System (GNSS) becomes increase in various applications, its reliability has been very important. However, in South Korea, Global Positioning System (GPS) jamming incident happened four times since 2010. GNSS signal is so weak that it is highly susceptible to all types of the jamming. GNSS jamming can cause serious damage in the safety-critical applications based on the GNSS. In this paper, we present the GNSS jamming signal propagation prediction simulator based on ITU-R P.1546 model. This simulator is developed for preventing or reducing the damage from the GNSS jamming attack by predicting the jamming propagation strength based on the geographical information in Korean peninsula.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.1-9
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• 2023

The problem of classifying a non-line-of-sight (NLOS) signal in a multipath channel is important to improve global navigation satellite system (GNSS) positioning accuracy in urban areas. Conventional deep learning-based NLOS signal classifiers use GNSS satellite measurements such as the carrier-to-noise-density ratio (CN_0), pseudorange, and elevation angle as inputs. However, there is a computational inefficiency with use of these measurements and the NLOS signal features expressed by the measurements are limited. In this paper, we propose a Convolutional Neural Network (CNN)-based NLOS signal classifier that receives successive Auto-correlation function (ACF) outputs according to a time-series, which is the most primitive output of GNSS signal processing. We compared the proposed classifier to other DL-based NLOS signal classifiers such as a multi-layer perceptron (MLP) and Gated Recurrent Unit (GRU) to show the superiority of the proposed classifier. The results show the proposed classifier does not require the navigation data extraction stage to classify the NLOS signals, and it has been verified that it has the best detection performance among all compared classifiers, with an accuracy of up to 97%.

• Journal of Satellite, Information and Communications
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• v.4 no.1
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• pp.36-44
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• 2009

The key technologies of GNSS receiver for GNSS sensor station are under development as a part of a GNSS ground station in ETRI. This paper presents the GNSS receiver implementation and signal processing result which is implemented based on FPGA to process the Galileo E1 and E5 signal. To verify the working and performance for GNSS receiver which is implemented based on FPGA, live signal received from GIOVE-B which is second test satellite is used. We gather GIOVE-B signal by using prototyping antenna and RF/IF units including IF-component. To verify Galileo E1 and E5 signal processing function from GIOVE-B, FPGA based signal processing module is implemented as a prototyping hardware board.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.231-238
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• 2007

This paper describes the availability of the forthcoming integrated GNSS(Global Navigation Positioning System) positioning that includes GPS(Global Positioning System), Galileo, and QZSS(Quasi-Zenith Satellites System). We built a signal propagation model that identifies direct, multipath, and diffraction signals, using the principles of specular reflection and ray tracing technique. The signal propagation model was combined with 3D GIS(three-dimensional geographic information system) in order to measure the satellite visibility and positioning error factors, such as the number of visible satellites, average elevation of visible satellites, optimized DOP(dilution of position) values, and the portion of multipath-producing satellites. Since Galileo and QZSS will not be fully operational until 2010, we used a simulation in comparing GPS and GNSS positioning for a $1km{\times}1km$ developed area in Shinjuku, Tokyo. To account for local terrain variation. we divided the target area into 40,000 $5m{\times}5m$ grid cells. The number of visible satellites and that of multipath-free satellites will be greatly increased in the integrated GNSS environment while the average elevation of visible satellites will be higher in the GPS positioning. Much decreased PDOP(position dilution of precision) values indicate the appropriate satellite/user geometry of the integrated GNSS; however, in dense urban areas, multipath mitigation will be more important than the satellite/user geometry. Thus, the efforts for applying current technologies of multipath mitigation to the future GNSS environment will be necessary.

• Journal of Positioning, Navigation, and Timing
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• v.1 no.1
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• pp.29-34
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• 2012

A software GNSS signal generator for the GPS L1/L2/L5 and Galileo E1/E5 signals is proposed in this paper. And this signal generator is designed and implemented with several components by considering the reuse and expansion of components for similar GNSS signals. The characteristics of the reusability of the components are confirmed with the carrier generation and the band-pass filter components. And the functionality of the GNSS multi-band IF signal generator is validated by using the commercial software GPS L1 receiver, and the performance of signal acquisition, tracking and accuracy of horizontal position error are analyzed for this validation. As a result, the GPS L1 signal generator operates successfully and it could be expected that other signal generators also operate well because most of components are the same as those of the GPS L1 signal generator.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.18 no.1
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• pp.11-18
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• 2010

GNSS(Global Navigation Satellite System) Ground Station performs GNSS signal acquisition and processing. This system generates error correction information and distributes them to GNSS users. GNSS Ground Station consists of sensor station which contains receiver and meteorological sensor, monitoring and control subsystem which monitors and controls sensor station, control center which generates error correction information, and uplink station which transmits correction information to navigation satellites. Monitoring and control subsystem acquires and processes navigation data from sensor station. The processed data is transmitted to GNSS control center. Monitoring and control subsystem consists of data acquisition module, data formatting and archiving module, data error correction module, navigation determination module, independent quality monitoring module, and system maintenance and management module. The independent quality monitoring module inspects navigation signal, data, and measurement. This paper introduces independent quality monitoring and performs the analysis using measurement data.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.3
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• pp.237-244
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• 2023

A signal generation simulator is an economical and useful solution in Global Navigation Satellite System (GNSS) receiver design and testing. A software-defined radio approach is widely used both in receivers and simulators, and its flexible structure to adopt to new signals is ideally suited to the testing of a receiver and signal processing algorithm in the signal design phase of a new satellite-based navigation system before the deployment of satellites in space. The generation of highly accurate delayed sampled codes is essential for generating signals in the simulator, where its sampling rate should be chosen to satisfy constraints such as Nyquist criteria and integer and non-commensurate properties in order not to cause any distortion of original signals. A high sampling rate increases the accuracy of code delay, but decreases the computational efficiency as well, and vice versa. Therefore, the selected sampling rate should be as low as possible while maintaining a certain level of code delay accuracy. This paper presents the lower limits of the sampling rate for GNSS signal generation simulators. In the simulation, two distinct code generation methods depending on the sampling position are evaluated in terms of accuracy versus computational efficiency to show the lower limit of the sampling rate for several GNSS signals.