High Accuracy Low Cost RTK/SINS for Land-Vehicles

Many situation demand a high precision, low cost and robust navigation for Land-Vehicles. Real Time Kinematic (RTK) satellite navigation is a technique that can provide up to centimeter level accuracy. But in the condition of poor visibility of satellites, the function of RTK is limited. To achieve a reliable high-precision navigation solution, this paper presents a RTK/SINS integration system based on the complementary features of RTK and SINS. The RTK is designed based on an open source program package RTKLIB. We use an innovation-based adaptive Kalman Filter with forget factor that filtering parameters can be adjusted by the change of GPS’ measurement noise in our project. Finally, the reliable and high accuracy of the low cost system is verified through several experiments. Introduction RTK is a precise satellites navigation, which uses measurements of the phase of the signal's carrier wave, rather than the information content of the signal, can providing up to cm-level position accuracy with the help of real time corrections that provided by a single reference station or continuously operating reference stations (CORSs). It has been used in many fields such as engineering measurement and position, mobile robot, mining, agriculture, and transportation. In the open area with enough visible satellites, the performance of RTK is trustworthy. However, the accuracy of RTK may lower and even lost when in the circumstances like urban canyon, under the elevated and in the tunnel. In order to obtain a reliable result of navigation, we use IMU (inertial measurement unit) integrated with RTK/GNSS to improve the performance. We use RTKLIB as a tool to process raw data from GPS receiver in order to acquire RTK solutions. RTKLIB is an open source program package for standard and precise positioning with GNSS developed by T. Takasu from Tokyo University of Marine Science and Technology, and distributed under the BSD 2-clause license. It is a compact and portable program library written in C to provide a standard platform for RTK-GPS applications. The library implements fundamental navigation functions and carrier-based relative positioning algorithms for RTK-GPS. It supports standard and precise positioning algorithms with GPS, GLONASS, Galileo, QZSS, BeiDou and SBAS, and also provides many library functions and APIs for GNSS data processing [1, 2]. Due to the price of Dual frequency RTK GPS receivers is too expensive, we choose the single frequency antennas and receivers in our project. While for get a high precision and robust navigation system for land-vehicles, an algorithm that integrating RTK and SINS (Strapdown Inertial Navigation System) effectively based on their respective characteristics is needed. KF (Kalman Filter) is often used to fusion the data of GPS and SINS and realize the integrated navigation system. But, the filtering accuracy will be decline even diverge if the system’s measurement noise is unstable [3]. To solve the problem, we use an innovation-based adaptive Kalman Filter with forget factor that measurement noise covariance matrix and process noise covariance matrix of the system can be updated real-time in this paper. On the basis of previous studies, we designed a MEMS sensors-based RTK/SINS integrated navigation system for land-vehicles. In the second part, the model of the 4th International Conference on Machinery, Materials and Information Technology Applications (ICMMITA 2016) Copyright © 2017, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Computer Science Research, volume 71