In this study, we developed a low-cost, high-precision vehicle navigation system for deep urban multipath environments using time-differenced carrier phase (TDCP) measurements. Although many studies are being conducted to navigate autonomous vehicles using the global positioning system (GPS), it is difficult to obtain accurate navigation solutions due to multipath errors in urban environments. Low-cost GPS receivers that determine the solution based on pseudorange measurements are vulnerable to multipath errors. We used carrier phase measurements that are more robust for multipath errors. Without correction information from reference stations, the limited information of a low-cost, single-frequency receiver makes it difficult to quickly and accurately determine integer ambiguity of carrier phase measurements. We used TDCP measurements to eliminate the need to determine integer ambiguity that is time-invariant and we combined TDCP-based GPS with an inertial navigation system to overcome deep urban multipath environments. Furthermore, we considered a cycle slip algorithm for its accuracy and a multi-constellation navigation system for its availability. The results of dynamic field tests in a deep urban area indicated that it could achieve horizontal accuracy of at the submeter level.

A single station-based positioning system, known as Mosaic/DME, is introduced. This new system has been designed for the Alternative PNT (APNT) solution to air services as it acts as a backup navigation system in case of GNSS outage. The Mosaic/DME is a single station consisting of conventional DME and multiple pseudolites. The DME is operated using two-way round signals for range measurements, with pseudolites broadcasting one-way continuous signals for carrier phase measurements. The receiver in the aircraft receives both signals and calculates its own position after the ambiguity resolution process. In this paper, the feasibility of this system is studied via two topics: the performance of the navigation accuracy and ambiguity resolution using the weighted dilution of precision and Monte Carlo simulations. The results conclude that this system satisfies the required navigation accuracy of the APNT and yields a very fast and easy ambiguity resolution. Copyright © 2015 Institute of Navigation.

Multipath errors are significantly challenging in radio navigation systems. In particular, multipath errors in indoor environments cause significant errors in the position domain because not only the building materials that surround the environment but also all objects inside the building can reflect the navigation signals. Multipath errors in outdoor environments, such as in global navigation satellite system (GNSS) signal applications, have been widely studied for precise positioning. However, multipath studies for indoor applications have rarely been conducted because of the complicated environment and the many objects made of various materials in small areas. In this study, multipath mitigation methods using a shallow neural network and a transfer learning-based deep neural network were respectively considered to overcome the complexity caused by the reflected signals in indoor environments. These methods classify each measurement according to whether the measurement exhibits a severe multipath error. Carrier-phase measurements broadcasted from the transmitter were used for the wavelet transform, and the magnitude values after the transform were used for neural network-based learning. Shallow and deep networks attain approximately 87.1% and 85.6% detection accuracies, respectively, and the positioning error can be reduced by 10.4% and 9.4%, respectively, after multipath mitigation.

A single-transmitter-based positioning system using an antenna array has been designed and developed to minimize the number of transmitters needed for environments where satellite-based navigation systems are unavailable. One of its suitable applications is for indoor navigation. The user receives the signals from the antenna array and calculates the position using the carrier-phase measurements. A key feature of the system is that the number of cycle ambiguity candidates is geometrically bounded. If the length of the antenna baseline is smaller than half the wavelength, the ambiguity resolution process is unnecessary. To improve the positioning performance for practical use, the antenna baseline must be enlarged. Even in this case, the cycle ambiguity resolution issue can be resolved fast and accurately. For instance, there are only nine candidates according to the setting of the study. To investigate the performance of the system, experiments for a dynamic rover using multiple “pseudolites,” pseudo-satellite transmitters, were conducted. In addition, low-cost inertial measurement unit (IMU) sensors were combined to investigate the improved positioning accuracy. Experimental results showed that positioning root-meansquare errors were 18 cm and 25 cm with IMU and without IMU, respectively, at the scale of a conventional meeting room. All integer-cycle ambiguities were solved accurately during the experiments, and more than 93% were resolved within 5 s.

SNUGLITE (Seoul National University Global navigation satellite system Laboratory satellITE) is a two-unit cube satellite (CubeSat) with dimensions 10 × 10 × 23 cm that requires an attitude system for missions and ground station telecommunication. A linear-quadratic-Gaussian-based optimal attitude system for the CubeSat platform has been developed using low-cost sensors, with the in-orbit verification of the attitude system being is one of main study objectives. Since launch, the SNUGLITE CubeSat has continuously broadcast in-orbit status information. In this study, a methodology for the analysis of in-orbit attitude estimation results using received data is presented, and this was achieved by comparing two sun-pointing vectors, i.e., the sun-pointing vector calculated using estimated attitude with the positions of the sun and the satellite and the reference vector generated by the power levels of the solar panels. Because the satellite position was required for the attitude analysis, the verification of the performance of the own-developed on-board Global Positioning System (GPS) receiver is also briefly described. Analyses indicate that the attitude estimation of the SNUGLITE CubeSat has achieved an in-orbit real-time pointing accuracy with a root mean square of 6.1°.