The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

Many spoofing detection studies have been conducted to cope with the most difficult types of deception among various disturbances of GPS, such as jamming, spoofing, and meaconing. In this paper, we propose a spoofing detection scheme based on elevation masked-relative received power between GPS L1 and L2 signals in a system using a multi-band array antenna. The proposed scheme focuses on enabling spoofing to be normally detected and minimizes the possibility of false detection in an environment where false alarms may occur due to pattern distortion among elements of an array antenna. The pattern distortion weakens the GPS signal strength at low elevation. It becomes confusing to detect a spoofing signal based on the relative power difference between GPS L1 and L2, especially when GPS L2 has weak signal strength. We propose design parameters for the relative power threshold including beamforming gain, the minimum received power difference between L1 and L2, and the patch antenna gain difference between L1 and L2. In addition, in order to eliminate the weak signal strength of GPS L2 in the spoofing detection process, we propose a rotation matrix that sets the elevation mask based on platform coordinates. Array antennas generally do not have high usefulness in commercial areas where receivers are operated alone, but are considered essential in military areas where GPS receivers are used together with signal processing for beamforming in the direction of GPS satellites. Through laboratory and live sky tests using the device under test, the proposed scheme with an elevation mask detects spoofing signals well and reduces the probability of false detection relative to that without the elevation mask.

Satellite navigation systems, with the exception of the GLObal NAvigation Satellite System (GLONASS), adopt ionosphere models and provide ionospheric coefficients to single-frequency users via navigation messages to correct ionospheric delay, the main source of positioning errors. A Global Navigation Satellite System (GNSS) mostly has its own ionospheric models: the Klobuchar model for Global Positioning System (GPS), the NeQuick-G model for Galileo, and the BeiDou Global Ionospheric delay correction Model (BDGIM) for BeiDou satellite navigation System (BDS)-3. On the other hand, a Regional Navigation Satellite System (RNSS) such as the Quasi-Zenith Satellite System (QZSS) and BDS-2 uses the Klobuchar Model rather than developing a new model. QZSS provides its own coefficients that are customized for its service area while BDS-2 slightly modifies the Klobuchar model to improve accuracy in the Asia-Pacific region. In addition, BDS broadcasts multiple ionospheric parameters depending on the satellites, unlike other systems. In this paper, we analyzed the different ionospheric models of GPS, QZSS, and BDS in Korea. The ionospheric models of QZSS and BDS-2, which are based in Asia, reduced error by at least 25.6% compared to GPS. However, QZSS was less accurate than GPS during geomagnetic storms or at low latitude. The accuracy of the models according to the BDS satellite orbit was also analyzed. The BDS-2 ionospheric model showed an error reduction of more than 5.9% when using GEO coefficients, while in BDS-3, the difference between satellites was within 0.01 m.

When calculating the user's position using satellite signals, the signals originating from the satellite pass through the ionosphere and troposphere to the user. In particular, the ionosphere delay error that occurs when passing through the ionosphere delays when the signal is transmitted, generating a pseudorange error and position error at a large rate. Therefore, to improve position accuracy, it is essential to correct the ionosphere layer error. In a receiver capable of receiving dual frequency, the ionosphere error can be eliminated through a double difference, but in a single frequency receiver, an ionosphere correction model transmitted from a Global Navigation Satellite System (GNSS) satellite is used. The popularly used Klobuchar model is designed to improve performance globally. As such, it does not perform perfectly in the Korea region. In this paper, the characteristics of the delay in the ionosphere in the Korean region are identified through an analysis of 10 years of data, and an improved ionosphere correction model for the Korean region is presented using the widely employed Klobuchar model. Through the proposed model, vertical position error can be improved by up to 40% relative to the original Klobuchar model in the Korea region.

Autonomous driving systems are likely to be operated in various complex environments. However, the well-known integrated Global Navigation Satellite System (GNSS)/Inertial Navigation System (INS), which is currently the major source for absolute position information, still has difficulties in accurate positioning in harsh signal environments such as urban canyons. To overcome these difficulties, integrated Visual/Inertial/GNSS (VIG) navigation systems have been extensively studied in various areas. Recently, a Compressed-State Constraint Kalman Filter (CSCKF)-based VIG navigation system (CSCKF-VIG) using a monocular camera, an Inertial Measurement Unit (IMU), and GNSS receivers has been studied with the aim of providing robust and accurate position information in urban areas. For this new filter-based navigation system, on the basis of time-propagation measurement fusion theory, unnecessary camera states are not required in the system state. This paper presents a performance evaluation of the CSCKF-VIG system compared to other conventional navigation systems. First, the CSCKF-VIG is introduced in detail compared to the well-known Multi-State Constraint Kalman Filter (MSCKF). The CSCKF-VIG system is then evaluated by a field experiment in different GNSS availability situations. The results show that accuracy is improved in the GNSS-degraded environment compared to that of the conventional systems.

In this paper, impacts of tropospheric delay gradient correction on PPP positioning performance were analyzed. A correction for tropospheric delay error due to the gradient was created and applied using external data, and reference station data were collected on a sunny day and a rainy day to analyze the GPS only dual-frequency PPP positioning results. As a result, on the sunny day, the convergence time was about 35 minutes and the final 3D position error was 10 cm, regardless of whether the correction for the tropospheric delay error by the gradient was applied. On the other hand, on the rainy day, the 3D position error converges only when the correction was applied, and the convergence time was about 34 minutes. Furthermore, the final 3D position error was improved from 30 cm to 10 cm. In addition, the analysis of the PPP by reference station location on the rainy day showed that the PPP positioning performance was improved when the correction was applied to a user located in an area where the weather changes.

In urban areas it can be difficult to utilize global navigation satellite systems (GNSS) due to signal reflections and blockages. It is thus crucial to detect reflected or blocked signals because they lead to significant degradation of GNSS positioning accuracy. In a previous study, a classifier for global positioning system (GPS) signal reception conditions was developed using three features and the support vector machine (SVM) algorithm. However, this classifier had limitations in its classification performance. Therefore, in this study, we developed an improved machine learning based method of classifying GPS signal reception conditions by including an additional feature with the existing features. Furthermore, we applied various machine learning classification algorithms. As a result, when tested with datasets collected in different environments than the training environment, the classification accuracy improved by nine percentage points compared to the existing method, reaching up to 58%.

Several experiments were carried out to analyze the impact of the modernized Global Positioning System (GPS) L2C signal on pseudorange-based point positioning. Three dual-frequency positioning algorithms, ionosphere-free linear combination, ionospheric error estimation, and simple integration, were used, and the results were compared with those of Standard Point Positioning (SPP). An analysis was conducted to determine the characteristics of each dual-frequency positioning method, the impact of the magnitude of ionospheric error, and receiver grade. Ionosphere-free and ionospheric error estimation methods can provide improved positioning accuracy relative to SPP because they are able to significantly reduce the ionospheric error. However, this result was possible only when the ionospheric error reduction effect was greater than the disadvantage of these dual-frequency positioning algorithms such as the increment of multipath and noise, impact of uncertainty of unknown parameter estimation. The RMSE of the simple integration algorithm was larger than that of SPP, because of the remaining ionospheric error. Even though the receiver grade was different, similar results were observed.

This study presents the performance analysis of real-time orbit determination and prediction for navigation message generation of Regional Navigation Satellite System (RNSS). Since the accuracy of ephemeris and clock correction in navigation message affects the positioning accuracy of the user, it is essential to construct a ground segment that can generate this information precisely when designing a new navigation satellite system. Based on a real-time architecture by an extended Kalman filter, we simulated orbit determination and prediction of RNSS satellites in order to assess the accuracy of orbit and clock prediction and signal-in-space ranging errors (SISRE). As a result of the simulation, the orbit and clock accuracy was at 0.5 m and 2 m levels for 24 hour determination and six hour prediction after the determination, respectively. From the prediction result, we verified that the SISRE of RNSS for six hour prediction was at a 1 m level.

In order to reserve frequency bands for stable operation of the Korean Positioning System (KPS), it must be demonstrated that the impact of interference caused by KPS on other services operating in the same bands is tolerable. The International Telecommunication Union (ITU) provides the radio regulations and a compatibility assessment methodology for the coexistence of different services in limited frequency resources. The purpose of this paper is to investigate the radio regulations regarding the compatibility issues between the KPS and other services sharing the same frequency bands. The results of the investigation show that the RNSS system can be operated in the L5-band under the condition that the Power Flux Density (PFD) and Aggregated Equivalent PFD (AEPFD) thresholds specified in the radio regulations are met. In addition, the ITU recommends that the interference-to-noise ratio (INR) protection criteria be met to prevent degradation of the performance of radar systems operating in the L2/L6-band. In the case of the S-band, coordination of allocations for RDSS space stations with respect to terrestrial services is not required if the PFD does not exceed regulated thresholds regulated by ITU.

The Korea Augmentation Satellite System (KASS) is the first satellite navigation enhancement system in Korea developed in compliance with international standards. Technologies accumulated during the development process should be spread to industries such as academia and serve as the basis for developing the domestic satellite navigation field. This paper introduces the development process from design to implementation, testing, and verification of KASS control systems (KCS). First, development standards, milestones, requirements, and interface standards are presented as KCS development methods, and major functional design, physical design, and hardware/software implementation are described based on the allocated requirements. Subsequently, the verification environment, procedures, and results of the development product are covered and the developed operational and maintenance procedures are described. In addition, based on the experience gained through the development, suggestions were made for beneficial technology development and organization when promoting satellite navigation projects in the future. Since this work has important historical value for the development of domestic satellite navigation, it is expected that the development results will be shared with academia and industry in the future and be used as basic data for similar development.

Time comparison techniques are required for generating and keeping Coordinated Universal Time (UTC) and to distribute standard clocks. These techniques play an important role in various fields, including science, finance, military, and communication. Among these techniques, Two-Way Satellite Time and Frequency Transfer (TWSTFT) ensures a relatively high accuracy, with a time comparison accuracy at a nanosecond level. However, TWSTFT systems have some limitations, such as the dependency on extra network links. In this paper, we propose an improved method for TWSTFT system operation and design a message structure for the suggestion. Additionally, we estimate the data rate and redundancy for the new TWSTFT signal with the designed message structure.