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An Optimization-Based GNSS/INS Integrated Navigation System
| Date | Stars |
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| 2026-07-24 | 644 |
| 2026-07-25 | 644 |
| 2026-07-28 | 644 |
| 2026-07-30 | 644 |
| 2026-08-06 | 644 |
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# OB_GINS ## Optimization-Based GNSS/INS Integrated Navigation System <img src="resource/OB_GINS.png" alt="OB_GINS" style="zoom:80%;" /> We open-source OB_GINS, an optimization-based GNSS/INS integrated navigation system. The main features of OB_GINS are as follows: - A sliding-window optimizer for GNSS/INS integration; - Abstract IMU-preintegration implementation, including: - The normal IMU preintegration without the Earth's rotation consideration; - The normal IMU/ODO preintegration; - The refined IMU preintegration with the Earth's rotation consideration; - The refined IMU/ODO preintegration; - Implementation of the marginalization; - Tools for attitude parameterization and coordinate frames; - Tools for file IO; **Authors:** Hailiang Tang, Xiaoji Niu, and Tisheng Zhang from the [Integrated and Intelligent Navigation (i2Nav) Group](http://www.i2nav.com/), Wuhan University. **Related Paper:** - Hailiang Tang, Tisheng Zhang, Xiaoji Niu, Jing Fan, and Jingnan Liu, “Impact of the Earth Rotation Compensation on MEMS-IMU Preintegration of Factor Graph Optimization,” *IEEE Sensors Journal*, 2022. - Le Chang, Xiaoji Niu, and Tianyi Liu, “GNSS/IMU/ODO/LiDAR-SLAM Integrated Navigation System Using IMU/ODO Pre-Integration,” *Sensors*, vol. 20, no. 17, p. 4702, Aug. 2020, doi: [10.3390/s20174702](https://doi.org/10.3390/s20174702). - Junxiang Jiang, Xiaoji Niu, and Jingnan Liu, “Improved IMU Preintegration with Gravity Change and Earth Rotation for Optimization-Based GNSS/VINS,” *Remote Sensing*, vol. 12, no. 18, p. 3048, Sep. 2020, doi: [10.3390/rs12183048](https://doi.org/10.3390/rs12183048). If you use this software for your academic research, please cite our related papers; and give acknowledgement like: ``` English version: “The authors would like to acknowledge Dr. Xiaoji Niu and the Integrated and Intelligent Navigation (i2Nav) group from Wuhan University for providing the OB_GINS software that was used in the paper.” 中文模板：“本文作者感谢武汉大学多源智能导航实验室和牛小骥教授开源的OB_GINS软件平台。” ``` **Contacts:** - For any technique problem, you can send an email to Dr. Hailiang Tang ([email protected]). - For Chinese users, we also provide a QQ group (**481173293**) for discussion. You are required to provide your organization and name. ## 1 Prerequisites ### 1.1 System and compiler We recommend you use Ubuntu 18.04 or Ubuntu 20.04 with the newest compiler (**gcc>=8.0** or **clang>=6.0**). ```shell # Ubuntu 18.04 # gcc-8 sudo apt install gcc-8 g++-8 # or clang # sudo apt install clang ``` ### 1.2 Ceres We use Ceres Solver to solve the non-linear least squares problem. The supported version is **Ceres Solver 2.0.0 or 2.1.0**. Please follow [Ceres installation instructions](http://ceres-solver.org/installation.html). ### 1.3 Eigen3 The supported version is **Eigen 3.3.7~3.3.9**. ```shell sudo apt install libeigen3-dev ``` ### 1.4 yaml-cpp ```shell sudo apt install libyaml-cpp-dev ``` ## 2 Build OB_GINS and run demo Once the prerequisites have been installed, you can clone this repository and build OB_GINS as follows: ```shell # Clone the repository git clone https://github.com/i2Nav-WHU/OB_GINS.git ~/ # Build OB_GINS cd ~/OB_GINS mkdir build && cd build # gcc cmake ../ -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=gcc-8 -DCMAKE_CXX_COMPILER=g++-8 # clang # cmake ../ -DCMAKE_BUILD_TYPE=Release -DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ make -j8 # Run demo dataset cd ~/OB_GINS ./bin/ob_gins ./dataset/ob_gins.yaml # Wait until the program finish ``` ## 3 Datasets ### 3.1 Demo dataset We offer a demo dataset with configuration file, which are located at **dataset** directory. ### 3.2 awesome-gins-datasets One can find our open-source datasets at **[awesome-gins-datasets](https://github.com/i2Nav-WHU/awesome-gins-datasets)**. ### 3.3 Your own dataset The data formats used in OB_GINS are the same as the formats defined at **[awesome-gins-datasets](https://github.com/i2Nav-WHU/awesome-gins-datasets)**. You can f
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