GPS/IMU/DMI组合导航方法研究 -- 西北工业大学学报,2018,36(2):396-402
论文:2018,Vol:36,Issue(2):396-402
引用本文:
高扬, 高逦, 乌萌, 王成宾. GPS/IMU/DMI组合导航方法研究[J]. 西北工业大学学报
Gao Yang, Gao Li, Wu Meng, Wang Chengbin. A GPS/IMU/DMI Combined Navigation Method[J]. Northwestern polytechnical university

GPS/IMU/DMI组合导航方法研究
高扬1,2, 高逦3, 乌萌1,2, 王成宾1,2
1. 地理信息工程国家重点实验室, 陕西 西安 710054;
2. 西安测绘研究所, 陕西 西安 710054;
3. 西北工业大学 计算机学院, 陕西 西安 710072
摘要:
利用可量测影像具有高精度空间位置信息的特点,提出了一种可量测影像与GPS、IMU组合导航方法。提出了系统框架,研究了可量测影像与道路网数据一体化组织方法,可量测影像与实时影像匹配定位算法,可量测影像与GPS、IMU联邦卡尔曼滤波导航模型。实验表明,新方法可以弥补车辆导航系统卫星信号失锁、惯性器件误差随时间累积发散等问题,提高了系统在复杂环境中定位精度和稳健性。
关键词:    可量测影像    影像匹配    卫星导航系统    惯性测量单元    联邦卡尔曼滤波   
A GPS/IMU/DMI Combined Navigation Method
Gao Yang1,2, Gao Li3, Wu Meng1,2, Wang Chengbin1,2
1. State Key Laboratory of Geo-Information Engineering, Xi'an 710054, China;
2. Xi'an Research Institute of Surveying and Mapping, Xi'an 710054, China;
3. School of Computer Science, Northwestern Polytechnical University, Xi'an 710072, China
Abstract:
According to the characteristics of DMI with high-precision position information, a navigation method combines DMIs with GPS and IMU is proposed in this paper. Firstly, the prototype system architecture is presented and its operational principle is discussed. Secondly, some key technologies are studied, which include integrated organization method of DMIs and road net data, the position method based on DMI matching with real-time image and the federal Kalman filter model with DMI, GPS and IMU. Finally, experimental results show that the proposed method can counteract GPS signal's unlocking problem and the inertial component's divergence for its error accumulation with time in a vehicle navigation system, whose positioning accuracy and robustness are improved in complex environment.
Key words:    digital measurable image    image matching    global positioning system    inertial measurement unit    federal Kalman filter   
收稿日期: 2017-04-20     修回日期:
DOI:
基金项目: 国家自然科学基金(60803158)资助
通讯作者:     Email:
作者简介: 高扬(1969-),西安测绘研究所高级工程师,主要从事卫星导航、地理信息系统的研究。
相关功能
PDF(3011KB) Free
打印本文
把本文推荐给朋友
作者相关文章
高扬  在本刊中的所有文章
高逦  在本刊中的所有文章
乌萌  在本刊中的所有文章
王成宾  在本刊中的所有文章

参考文献:
[1] Dupuis Y, Merriaux P, Subirats P, et al. GPS-Based Preliminary Map Estimation for Autonomous Vehicle Mission Preparation[C]//Internativonal Conference on Intelligent Robots and Systems, 2014
[2] Yun Heecheon. Applicability Estimation of Mobile Mapping System for Road Management[J]. Contemporary Engineering Sciences, 2014, 7(24):1407-1414
[3] Suhr Jaekyu, Jang Jeungin, Min Daehong, et al. Sensor Fusion-Based Low-Cost Vehicle Localization System for Complex Urban Environments[J]. IEEE Trans on Intelligent Trans Systems, 2017, 18(5):1078-1086
[4] Meng Xiaoli, Wang Heng, Liu Bingbing. A Robust Vehicle Localization Approach Based on GNSS/IMU/DMI/LiDAR Sensor Fusion for Autonomous Vehicles[J]. Sensors, 2017, 17:2140
[5] 李德仁,刘立坤,邵振峰. 集成倾斜航空摄影测量和地面移动测量技术的城市环境监测[J]. 武汉大学学报:信息科学版,2015, 40(4):427-435 Li Deren, Liu Likun, Shao Zhenfeng. An Integration of Aerial Oblique Photogrammetry and Mobile Mapping System for Urban Geographical Conditions Monitoring[J]. Geomatics and Information Science of Wuhan University, 2015, 40(4):427-435(in Chinese)
[6] 卢秀山,滕腾,刘如飞. 移动测量、地理信息更新与城市管理智能化[J]. 测绘学报, 2017, 46(10):1592-1597 Lu Xiushan, Teng Teng, Liu Rufei. Mobile Mapping, Geographic Information Update and Urban Management Intelligence[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(10):1592-1597(in Chinese)
[7] 高扬,王成宾,乌萌. 一种基于可量测影像的实景导航数据组织模型[J]. 测绘科学与工程, 2014, 34(2):50-56 Gao Yang, Wang Chengbin, Wu Meng. A Vision Navigation Data Model Based on Digital Measurable Image[J]. Geomatics Science and Engineering, 2014, 34(2):50-56(in Chinese)
[8] 李德仁. 论可量测实景影像的概念与应用——从4D产品到5D产品[J]. 测绘科学, 2007, 32(4):5-7 Li Deren. On Concept and Application of Digital Measurable Images-from 4D Production to 5D Production[J]. Science of Surveying and Mapping, 2007, 32(4):5-7(in Chinese)
[9] 李德仁, 胡庆武. 基于可量测实景影像的空间信息服务[J]. 武汉大学学报:信息科学版, 2007, 32(5):377-380 Li Deren, Hu Qingwu. Digital Measurable Image Based Geo-Spatial Information Service[J]. Geomatics and Information Science of Wuhan University, 2007, 32(5):377-380(in Chinese)
[10] Lowe D G. Object Recognition from Local Scale-Invariant Features[C]//International Conference on Computer Vision, Corfu Greece,1999:1758-1762
[11] Bay H, Tuytelaars T, Van Gool L. SURF:Speeded up Robust Features[C]//European Conference on Computer Vision, 2006:1562-1568
[12] Matas J, Chum O,Urban M, et.al. Robust Wide Baseline Stereo from Maximally Stable Extremal Regions[C]//British Machine Vision Conference, 2002:844-853
[13] Iijima T. Basic Theory of Pattern Normalization(for the Case of a Typical One Dimensional Pattern)[J]. Bulletin of the Electrotechnical Laboratory, 1962, 26:368-388
[14] Martin A Fischler, Robert C Bolles. Random Sample Consensus:a Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography[J]. Communication of the ACM, 1981:568-569