Fields of high-precision positioning applications are growing fast across the mass market worldwide. Accordingly, the industry is focusing on developing methods of applying State-Space Representation (SSR) corrections on low-cost GNSS receivers. Among SSR correction types, this paper analyzes Safe Position Augmentation for Real Time Navigation (SPARTN) messages being offered by the SAfe and Precise CORrection DAta (SAPCORDA) company and validates positioning algorithms based on them. The first part of this paper introduces the SPARTN format in detail. Then, procedures on how to apply Basic-Precision Atmosphere Correction (BPAC) and High-Precision Atmosphere Correction (HPAC) messages are described. BPAC and HPAC messages are used for correcting satellite clock errors, satellite orbit errors, satellite signal biases and also ionospheric and tropospheric delays. Accuracies of positioning algorithms utilizing SPARTN messages were validated with two types of positioning strategies: Code-PPP using GPS pseudorange measurements and PPP-RTK including carrier phase measurements. In these performance checkups, only single-frequency measurements have been used and integer ambiguities were estimated as float numbers instead of fixed integers. The result shows that, with BPAC and HPAC corrections, the horizontal accuracy is 46% and 63% higher, respectively, compared to that obtained without application of SPARTN corrections. Also, the average horizontal and vertical RMSE values with HPAC are 17 cm and 27 cm, respectively.

The extended Kalman filter (EKF) is widely used for global navigation satellite system (GNSS) applications. It is difficult to obtain precise positions with an EKF one-way (forward or backward) filter. In this paper, we propose an EKF smoother to improve the positioning accuracy by integrating forward and backward filters. For the EKF smoother experiment, we performed PPP using GNSS data received at the DAEJ reference station for a month. The effectiveness of the proposed approach is validated with multi-GNSS kinematic PPP experiments. The EKF smoother showed 35%, 6%, and 22% improvement in east, north, and up directions, respectively. In addition, accurate tropospheric zenith total delay (ZTD) values were calculated by a smoother. Therefore, the results from EKF smoother demonstrate that better accuracy of position can be achieved.

In this paper, a fully reconfigurable Software Defined Radio (SDR) for multi-constellation and multi-frequency Global Navigation Satellite System (GNSS) receivers is presented. The reconfigurability with respect to the data structure, variability of signal and receiver parameters, and receiver's internal functionality is presented. The configuration file, that is modified to lead to an entirely different operation of the SDR in response to specific target signal scenarios, directly determines the operating characteristics of the SDR. In this manner, receiver designers can effectively reduce the effort to develop many different combinations of multi-constellation and/or multi-frequency GNSS receivers. Finally, the implementation of the presented fully reconfigurable SDR is included with the experimental processing results such as acquisition, tracking, navigation for the received signals in the realistic fields.

A series of experiments have been carried out by using National Geographic Information Institute(NGII)'s Continuously Operating Reference Station (CORS) data with various strategies to analyze the impact of multi-GNSS measurements on baseline processing. The results of baseline processing were compared in terms of ambiguity fixing rate, precision, and hypothesis tests were conducted to confirm the statistical difference. The combination of multi-GNSS measurements has helped to improve ambiguity fixing rate, especially under harsh positioning environments. Combination of GPS, Galileo, BeiDou could get better precision than that of GPS, GLONASS, Galileo, and adding QZSS made the baseline solution's vertical component more precisely. The hypothesis tests have statistically confirmed that the inclusion of the multi-GNSS in the baseline processing enables not only to reduce field observation time length but also to enhance the solution's precision. However, it is of interest to notice that results of the baseline solution are dependent upon the software used. Hence, comprehensive studies should be performed shortly to derive the best practice to select the appropriate software.

The Distance Measuring Equipment (DME) is a ground-based aircraft navigation system and is considered as an infrastructure that ensures resilient aircraft navigation capability during the event of a Global Navigation Satellite System (GNSS) outage. The main problem of DME as a GNSS back up is a poor positioning accuracy that often reaches over 100 m. In this paper, a novel approach of applying deep reinforcement learning to a DME pulse design is introduced to improve the DME distance measuring accuracy. This method is designed to develop multipath-resistant DME pulses that comply with current DME specifications. In the research, a Markov Decision Process (MDP) for DME pulse design is set using pulse shape requirements and a timing error. Based on the designed MDP, we created an Environment called PulseEnv, which allows the agent representing a DME pulse shape to explore continuous space using the Soft Actor Critical (SAC) reinforcement learning algorithm.

In this paper, we propose a method to improve the positioning accuracy of TOA based indoor positioning system in NLOS environments. TOA based indoor positioning systems have been studied mostly considering LOS environments. However, it is almost impossible to maintain the LOS environments due to obstacles such as people, furniture, walls, and so on. The proposed method in this study compensates the range error caused by the NLOS environments. We confirmed that positioning accuracy of a proposed method is improved than conventional algorithms through simulation and field test.

The Angle-of-Arrival (AOA) estimation in real time is one of core technologies for the real-time tracking system, such as a radar or a satellite. Although AOA estimation algorithms for various antenna types have been studied, most of them are for the single-shaped array antenna suitable to the specific frequency. In this paper, we propose the cascade AOA estimation algorithm for the combined array antenna with Uniform Rectangular Frame Array (URFA) and Uniform Circular Array (UCA), with the excellent performance for various frequencies. The proposed technique is consisted of Capon for roughly finding AOA groups with multiple signal AOAs and Beamspace Multiple Signal Classification (MUSIC) for estimating the detailed signal AOA in the AOA group, for the combined array antenna. In addition, we provide computer simulation results for verifying the estimation performance of the proposed algorithm.

In this paper, we described configuration and construction of infrastructure for the KASS Reference Station (KRS), subsystem of Korea Augmentation Satellite System (KASS). KASS system consists of three subsystems(KRS, Mission Control Center (MCC), KASS Uplink Station (KUS)). One of these subsystems, KRS receives GNSS data for generating range error and integrity verification and sends to MCC. It is needed to antenna facilities for mounting GNSS antenna and shelter for operating KRS and infra equipment(power and network system, lightning and grounding system, fire extinguish) for operating KRS. For this reason, we have established the requirements for KRS infrastructure and constructed infrastructure for KRS to meet the requirements of KRS infrastructure.

According to the Korea Augmentation Satellite System (KASS) system milestone, Site Acceptance Test (SAT) has three steps test until the end of the project. SAT#1 is the first time of SAT steps and verify the KASS Reference Station (KRS) and Sub System (S/S) for the monitoring and controllable. After the equipment and software were installed at the Mission Control Center (MCC) with Central Monitoring and Control Simulator (CMS) for the SAT#1, the 1:1 test was progressed when the KRS and S/S are ready to test. SAT#1 has a 10 steps test case and it was progressed each KRS sites. The test was finished throughout the real-time monitoring and the data collection including the data analysis all of the 7 KRS sites. Finally SAT#1 was completed on December 2020 with successfully.

In order to mitigate the vulnerability of the satellite navigation system against radio frequency interference, South Korea has been developing advanced terrestrial navigation system (eLoran) technology since 2016. The eLoran system synchronizes the transmission time of the pulse used in the existing Loran-C system with UTC and transmits correction information that can improve the position error. The eLoran system is known to reduce the position error of about 460 m of the existing Loran-C system to 20 m, and for this, the transmitter must be able to transmit eLoran signals according to more stringent standards. For this reason, an international standard that further developed the Loran-C signal standard established by US Coast Guard was established by Society of Automotive Engineers (SAE) International. In this paper, based on the analysis of the SAE9990 document, the international standard for eLoran transmission signals, a standard inspection process was produced to check whether the eLoran transmitter is transmitting signals in accordance with the standard.