As the demand on the precise positioning for the moving objects has been increased in the various industry field, many studies have been conducted to analyze real time kinematic technique and its practical usage.The main purpose of this study is to analyze the possibility of Network-RTK(VRS) in real-time kinematic positioning. So, the accuracy analysis has been conducted by comparing the Network-RTK(VRS) position with respect to the RTK position.As a result, Network-RTK(VRS) based on kinematic positioning has centimeter level of RMS in the ideal environment compared to RTK positioning. However, when the integer ambiguities was lost, the accuracy of Network-RTK was meter level. At that time, the quality value has been changed dramatically and shows big correlation with accuracy. When the position and height quality values are within 0.1m, the RMS of the horizontal and vertical position appears better than 10cm and 20cm, respectively. However, if the quality value is over 0.1m, the RMS increases to larger than a meter. Therefore, it is recommended to check the quality value when conducting Network-RTK(VRS) kinematic positioning to get the centimeter level accuracy.
Based on the GPS/IMU integration, the car navigation has unstable conditions as well as drastically reduces accuracies in urban region. Nowadays, many cars mounted the camera to record driving states. If the ground coordinates of street furniture are known, the position and attitude of camera can be determined through SPR (Single Photo Resection). Therefore, an estimated position and attitude from SPR can be applied measurements in Kalman filter for updating errors of navigation solutions from GPS/IMU integration. In this study, the GPS/ IMU/SPR integration algorithm was developed in loosely coupled modes through extended Kalman filters. Also, in order to analyze performances of GPS/IMU/SPR, simulation tests were conducted in GPS signal reception environments and the GCPs (Ground Control Points) distributions. In fact, the position and attitude gathered from GPS/IMU/SPR integration are more precise than the position and attitude from GPS/IMU integration. When IPs (image points), corresponded to GCPs, were concentrated in the center of image, the position error in the optical axis respectively increased. To understand effects from SPR, we plan to carry additional test on the magnitude of GCP, IP and initial exterior orientation errors. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.