This paper proposes a signal merging algorithm to increase the signal-to-noise ratio (SNR) of a GPS correlator output to estimate the roll angle of a rotating vehicle in a weak GPS signal environment. Rotation Locked Loop (RLL) algorithm is used to estimate a roll angle using the characteristics that the power of the GPS signal measured at the receiver of a rotating vehicle varies periodically. First, delay times are calculated to synchronize GPS signals using satellites' and receiver's positions and the rotation frequency of a vehicle, and then correlator outputs are delayed in time and merged with each other, resulting in the increase of an SNR in a correlator output. Finally, simulations are conducted and the performance of the proposed algorithm is validated.

In this paper, an efficient and robust localization algorithm using Receiver Signal Strength Difference (RSSD) for a non-cooperative RF emitter is given. The proposed algorithm firstly calculate the center point and radius of Apollonius's circles and then estimate the intersection point of the circles based on Time of Arrival concept. And this paper also compares the performance of RSSD localization algorithms such as Non-linear Least Squares and Linearized Least Squares by Lines of Position (LOP) with the proposed algorithm. And some conclusions have been reached regarding the relative accuracy, robustness and computational cost of these algorithms.

In this study, a system that precisely determines the heave of ship hull was designed using time-differenced GNSS carrier phase measurement, and the performance was examined. First, a technique that calculates precise position relative to the original position based on TDCP measurement for point positioning using only one receiver was implemented. Second, to eliminate the long-cycle drift error occurring due to the measurement error that has not been completely removed by time-differencing, an easily implementable high-pass filter was designed, and the optimum coefficient was determined through an experiment. In a static experiment based on the precise heave measurement system implemented using low-cost commercial GNSS receiver and PC, the heave could be measured with a precision of 2 cm standard deviation. In addition, in a dynamic experiment where it moved up and down with an amplitude of 48 cm and a cycle of 20 seconds, precise heave without drift error could be determined. The system proposed in this study can be easily used for many applications, such as the altitude correction of fish detection radar.

The position of autonomous driving vehicle is basically acquired through the global positioning system (GPS). However, GPS signals cannot be received in tunnels. Due to this limitation, localization of autonomous driving vehicles can be made through sensors mounted on them. In particular, a 3D Light Detection and Ranging (LIDAR) system is used for longitudinal position error correction. Few feature points and structures that can be used for localization of vehicles are available in tunnels. Since lanes in the road are normally marked by solid line, it cannot be used to recognize a longitudinal position. In addition, only a small number of structures that are separated from the tunnel walls such as sign boards or jet fans are available. Thus, it is necessary to extract usable information from tunnels to recognize a longitudinal position. In this paper, fire hydrants and evacuation guide lights attached at both sides of tunnel walls were used to recognize a longitudinal position. These structures have highly distinctive reflectivity from the surrounding walls, which can be distinguished using LIDAR reflectivity data. Furthermore, reflectivity information of tunnel walls was fused with the road surface reflectivity map to generate a synthetic reflectivity map. When the synthetic reflectivity map was used, localization of vehicles was able through correlation matching with the local maps generated from the current LIDAR data. The experiments were conducted at an expressway including Maseong Tunnel (approximately 1.5 km long). The experiment results showed that the root mean square (RMS) position errors in lateral and longitudinal directions were 0.19 m and 0.35 m, respectively, exhibiting precise localization accuracy.

In this paper, a simplified Cubature Kalman Filter (SCKF) is proposed to reduce the computation load of CKF, which is then used as a filter for transfer alignment of shipboard INS. CKF is an approximate Bayesian filter that can be applied to non-linear systems. When an initial estimation error is large, convergence characteristic of the CKF is more stable than that of the Extended Kalman Filter (EKF), and the reliability of the filter operation is more ensured than that of the Unscented Kalman Filter (UKF). However, when a system degree is large, the computation amount of CKF is also increased significantly, becoming a burden on real-time implementation in embedded systems. A simplified CKF is proposed to address this problem. This filter is applied to shipboard inertial navigation system (INS) transfer alignment. In the filter design for transfer alignment, measurement type and measurement update rate should be determined first, and if an application target is a ship, lever-arm problem, flexure of the hull, and asynchronous time problem between Master Inertial Navigation System (MINS) and Slave Inertial Navigation System (SINS) should be taken into consideration. In this paper, a transfer alignment filter based on SCKF is designed by considering these problems, and its performance is validated based on simulations.

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

A 2U cube satellite called SNUGLITE has been developed by GNSS Research Laboratory in Seoul National University. Its main mission is to perform actual operation by mounting dual-frequency global positioning system (GPS) receivers. Its scientific mission aims to observe space environments and collect data. It is essential for a cube satellite to control an Earth-oriented attitude for reliable and successful data transmission and reception. To this end, an attitude estimation and control algorithm, Attitude Determination and Control System (ADCS), has been implemented in the on-board computer (OBC) processor in real time. In this paper, the Extended Kalman Filter (EKF) was employed as the attitude estimation algorithm. For the attitude control technique, the Linear Quadratic Gaussian (LQG) was utilized. The algorithm was verified through the processor in the loop simulation (PILS) procedure. To validate the ADCS algorithm in the ground, the experimental verification via a single axis Hardware-in-the-loop simulation (HILS) was used due to the simplicity and cost effectiveness, rather than using the 3-axis HILS verification (Schwartz et al. 2003) with complex air-bearing mechanism design and high cost.

Multi-Global Navigation Satellite System (GNSS) can significantly improve the positioning accuracy and convergence speed. The reliability and availability of multi-GNSS precise point positioning (PPP) is steadily increasing with the rapid development of GNSS satellites. In this study, multi-GNSS PPP analysis is performed to compare the positioning precision by processing the observations from different GNSS systems (GPS, GLONASS, Galileo and BeiDou). To improve the positioning performance of the multi-GNSS PPP, we employed the weighed measurement noise (WMN) method. After applying WMN method to multi-GNSS PPP, positioning precision is improved by approximately 26.3% compared to the GPS only solutions, and by approximately 9.1% compared to combined GPS, GLONASS, and Galileo PPP.

Ellipsodially referenced survey (ERS) is considered as one of the challenging issues in the hydrographic surveys due to the fact that the bathymetric data collected by this technique can be readily transformed either to the geodetic or the chart datum by application of some geoscientific models. Global Navigation Satellite Systems (GNSS) is a preferred technique to determine the ellipsoidal height of a vessel reference point (RP) because it provides cost-effective and unprecedentedly accurate positioning solutions. Especially, the GNSS-derived heights include heave and dynamic draft of a vessel, so as for the reduced bathymetric solutions to be potentially free from these corrections. Although over the last few decades, differential GNSS (DGNSS) has been widely adopted in the bathymetric surveys, it only provides limited accuracy of the vertical component. This technical barrier can be effectively overcome by adopting the so-called GNSS carrier phase (CPH) based techniques, enhancing accuracy of the height solution up to few centimeters. From the positioning algorithm standpoint, the CPH-based techniques are categorized under absolute and relative positioning in post-processing mode; the former is precise point positioning (PPP) correcting errors by the global or regional models, the latter is post-processed kinematic positioning (PPK) that uses the differencing technique to common error sources between two receivers. This study has focused on assessment of achievable accuracy of the ellipsoidal heights obtained from these CPH-based techniques with a view to their applications to hydrographic surveys where project area is, especially, few tens to hundreds kilometers away from the shore. Some field trials have been designed and performed so as to collect GNSS observables on static and kinematic mode. In this paper, details of these tests and processed results are presented and discussed.