Abstract
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.
Highlights
The global positioning system (GPS) is widely employed to determine the position, velocity, and time (PVT) information of users on Earth based on signals broadcast through GPS satellites in space
The 3σ results demonstrate the performance improvement by 10%, 30%, and 60% in the inertial measurement unit (IMU) sensor specification case, 2.5× case, and 5× case, respectively
Because the time-differenced carrier phase (TDCP) contains current and previous information that violate that the improvements in accuracy are less than those in the simulation is that the maneuvers of the the format of the usual Kalman filter (KF), approximations have been used to design new measurement equations in user as well as the road environment, which cause noise, were better than in the simulation most studies
Summary
The global positioning system (GPS) is widely employed to determine the position, velocity, and time (PVT) information of users on Earth based on signals broadcast through GPS satellites in space. Estimated the relative position in terms of the phase-derived position increment (PDPI) using TDCP measurements and improved the positioning accuracy by applying additional PDPI measurements in the conventional TC method. These studies dealt with how to model TDCP measurements, as well as the accuracy of the results, without addressing reliability issues, such as covariance bounding. We propose a TDCP-based integrated GPS/INS considering noise correlation. A delayed state filter that considers correlated process and measurement noise is utilized to improve the accuracy and reliability of the GPS/INS using TDCP measurements, unlike in previous methods.
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