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.

In this study, we combined a time-differenced carrier phase (TDCP)-based global positioning system (GPS) with an inertial navigation system (INS) to form an integrated system that appropriately considers noise correlation. The TDCP-based navigation system can determine positions precisely based on high-quality carrier phase measurements without difficulty resolving integer ambiguity. Because the TDCP system contains current and previous information that violate the format of the conventional Kalman filter, a delayed state filter that considers the correlation between process and measurement noise is utilized to improve the accuracy and reliability of the TDCP-based GPS/INS. The results of a dynamic simulation and an experiment conducted to verify the efficacy of the proposed system indicate that it can achieve performance improvements of up to 70% and 60%, respectively, compared to the conventional algorithm.

When a user receiver is tracking an authentic signal, a spoofing signal can be transmitted to the user antenna. The question is under what conditions does the tracking point of the receiver move from the authentic signal to the spoofing signal? In this study, we develop a spoofing process equation (SPE) that can be used to calculate the tracking point of the delay lock loop (DLL) at regular chip intervals for the entire spoofing process. The condition for a successful spoofing signal is analyzed using the SPE. To derive the SPE, parameters, such as the signal strength, sweep velocity, loop filter order, and DLL bandwidth are considered. The success or failure of a spoofing attack is determined for a specific spoofing signal using the SPE. In addition, a correlation between each parameter for a successful spoofing attack could be obtained through the SPE. The simulation results show that the SPE performance is largely consistent with that of general DLL methods, even though the computational load of SPE is very low.

Generally, GNSS-based indoor navigation systems use repeaters or pseudolites. However, these methods are vulnerable to multipath errors and require additional information, including the repeater or pseudolite position. In this study, we propose a novel one-way indoor positioning system using GNSS signal transmitters. Our system uses paired transmitters, each of which broadcasts the same set of satellite signals. The autocorrelation functions of the combined signals are analyzed as the overlap of each individual autocorrelation function. The estimated position can be determined along the track between the transmitters. The multipath error is absorbed by the clock bias and does not cause position bias error. Furthermore, the proposed system can be applied in current commercial GNSS receivers directly. A theoretical analysis of the pseudorange, user position, multipath error, and signal power is included and supported by simulation results. A field test was conducted to confirm the feasibility of the proposed system.

This study proposed a wide area protection method using global navigation satellite system (GNSS) interference signals against numerous unintentional drones. The defensive GNSS signals generated by a single signal generator sweep the authentic GNSS signals so that the signal tracking loop tracks the defensive signals for the drones to be guided to a safe zone. The proposed algorithm performs a sweep in the measurement domain by adjusting the time offset of the signal generator, which makes it possible to sweep a wider area. In this fundamental study to confirm the possibility of wide area protection, we investigated the signal generation method for the transition of signal tracking locks from authentic to defensive signals in situations where a signal generator does not know the drones’ positions. We examined the time discrepancy between the authentic and defensive signals, and the worst-case analysis to determine the minimum sweep range of the time offset. The determined minimum sweep range of the time offset. The determined minimum sweep range overcomes the influence of time discrepancy and unconditionally deceives multiple drones regardless of the satellite’s position, drones’ trajectories, and entry timing. To deceive drones approaching a sphere with a radius of 1 km, the minimum sweep range is approximately 6 and 3 km when the signal generator is 0 and 2 km away from the center of the swethe region respectively. The simulation results verified the theoretical analysis and showed that the defensive signals transmitted by one signal generator can deceive multiple drones to the center of the sweep region, which is the intended location.