Global Navigation Satellite System (GNSS) provides location information using signals from multiple satellites. However, a spoofing attack that forges signals or retransmits delayed signals may cause errors in the location information. To prevent such attacks, authentication protocols considering the navigation message structure of each GNSS can be used. In this paper, we analyze the authentication protocols of Global Positioning System (GPS), Galileo, and BeiDou, and compare the performance of Navigation Message Authentication (NMA) of the above systems, using several performance indicators. According to our analysis, authentication protocols are similar in terms of performing NMA and using Elliptic Curve Digital Signature Algorithm (ECDSA). On the other hand, they are different in several ways, for example, whether to perform Spreading Code Authentication (SCA), whether to use digital certificates and whether to use Timed Efficient Stream Loss-tolerant Authentication (TESLA). According to our quantitative analysis, the authentication protocol of Galileo has the shortest time between authentications and time to first authenticated fix. We also show that the larger the sum of the navigation message bits and authentication bits, the more severely affected are the time between authentications and the time to first authenticated fix.

Fast Fourier transform (FFT)-based parallel acquisition techniques with reduced computational complexity have been widely used for the acquisition of binary phase shift keying (BPSK) global positioning system (GPS) signals. In this paper, we propose a low computational FFT-based fine acquisition technique, for binary offset carrier (BOC) modulated BPSK signals, that depending on the subcarrier-to-code chip rate ratio (SCR) selectively utilizes the computationally efficient frequency-domain realization of the BPSK-like technique and two-dimensional compressed correlator (BOC-TDCC) technique in the first stage in order to achieve a fast coarse acquisition and accomplishes a fine acquisition in the second stage. It is analyzed and demonstrated that the proposed technique requires much smaller mean fine acquisition computation (MFAC) than the conventional FFT-based BOC acquisition techniques. The proposed technique is one of the first techniques that achieves a fast FFT-based fine acquisition of BOC signals with a slight loss of detection probability. Therefore, the proposed technique is beneficial for the receivers to make a quick position fix when there are plenty of strong (i.e., line-of-sight) GNSS satellites to be searched.

The eLoran system is a high-power terrestrial navigation system that is recognized as the most appropriate alternative to complement the GNSS's vulnerability to radio frequency interference. Accordingly, Korea has conducted eLoran technology development projects since 2016. The eLoran system developed in Korea provides 20 m positioning accuracy to maritime user in Incheon and Pyeongtaek harbor. To accurately calculate the position with the eLoran signal, it is necessary to apply a compensation method that mitigates the propagation delay. In this paper, we develop the compensation method to mitigate the eLoran signal propagation delay and evaluate the positioning performance in Incheon harbor. The propagation delay due to the terrain characteristics is pre-surveyed and stored in the user receiver. Real-time fluctuations in propagation delay compared to the pre-stored data are mitigated by the temporal correction generated at a nearby differential Loran station. Finally, two performance evaluation tests were performed to verify the positioning accuracy of the Korean eLoran system. The first test took place in December 2020 and the second in April 2021. As a result, the Korean eLoran service has been confirmed to provide 20 m location accuracy without GPS.

In this paper, we analyze the Non-Holonomic Constraint (NHC) satisfaction of Inertial Navigation System (INS) for vehicular navigation according to Inertial Measurement Unit (IMU) location. In INS-based vehicle navigation, NHC information is widely used to improve INS performance. That is, the error of the INS can be compensated under the condition that the velocity in the body coordinate system of the vehicle occurs only in the forward direction. In this case, the condition that the vehicle's wheels do not slip and the vehicle rotates with the center of the IMU must be satisfied. However, the rotation of the vehicle is rotated by the steering wheel which is controlled based on the Ackermann geometry, where the center of rotation of the vehicle exists outside the vehicle. Due to this, a phenomenon occurs that the NHC is not satisfied depending on the mounting position of the IMU. In this paper, we analyze this problem based on Ackermann geometry and prove the analysis result based on simulation.

In this paper, a dual foot (DF)-PDR system is proposed for the fusion of integration (IA)-based PDR systems independently applied on both shoes. The horizontal positions of the two shoes estimated from each PDR system are fused based on a particle filter. The proposed method bounds the position error even if the walking time increases without an additional sensor. The distribution of particles is a non-Gaussian distribution to express the lateral error due to systematic drift. Assuming that the shoe position is the pedestrian position, the multi-modal position distribution can be fused into one using the Gaussian sum. The fused pedestrian position is used as a measurement of each particle filter so that the position error is corrected. As a result, experimental results show that position of pedestrians can be effectively estimated by using only the inertial sensors attached to both shoes.

In this paper, we propose a method for estimating the error of the Ultra-Wideband (UWB) distance measurement using the channel impulse response (CIR) of the UWB signal based on machine learning. Due to the recent demand for indoor location-based services, wireless signal-based localization technologies are being studied, such as UWB, Wi-Fi, and Bluetooth. The constructive obstacles constituting the indoor environment make the distance measurement of UWB inaccurate, which lowers the indoor localization accuracy. Therefore, we apply machine learning to learn the characteristics of UWB signals and estimate the error of UWB distance measurements. In addition, the performance of the proposed algorithm is analyzed through experiments in an indoor environment composed of various walls.

Korea Augmentation Satellite System (KASS) is a Satellite Based Augmentation System (SBAS) system under development in South Korea and aims to provide air navigation services after 2023. In order to provide reliable service, detailed design for the operation of this system is required. This paper proposes a detailed operation-based designs based on mission, architecture, operation definition of the system. For the stable operation of the system, an operation organization was designed and operation activities were classified in consideration of the architecture and function of the system. Detailed operation procedures were designed according to this classification and operation procedures related to the command and configuration of subsystem were verified on the Integration, Verification and Qualification (IVQ) platform for integrated testing and verification. The proposed operation concepts and procedures will be continuously confirmed and verified during verification, qualification and service preparation, and will be updated event after official KASS service.