Cooperative Inertial Navigation for GNSS-Challenged Vehicular Environments

被引:48
|
作者
Alam, Nima [1 ]
Kealy, Allison [2 ]
Dempster, Andrew G. [3 ]
机构
[1] Caterpillar Trimble Control Technol, Dayton, OH 45424 USA
[2] Univ Melbourne, Melbourne Sch Engn, Dept Infrastruct Engn, Melbourne, Vic 3010, Australia
[3] Univ New S Wales, Sch Elect Engn & Telecommun, Sydney, NSW 2052, Australia
关键词
Carrier frequency offset (CFO); cooperative inertial navigation (CIN); cooperative positioning (CP); inertial navigation system (INS); POSITIONING ENHANCEMENT; FREQUENCY OFFSET; SYSTEMS; DSRC;
D O I
10.1109/TITS.2013.2261063
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Cooperative positioning (CP) is an approach for positioning and/or positioning enhancement among a number of participants, which communicate and fuse their position-related information. Due to the shortcomings of Global Navigation Satellite Systems (GNSSs), modern CP approaches are considered for improving vehicular positioning where the GNSS cannot address the requirements of the specific applications such as collision avoidance or lane-level positioning. An inertial navigation system (INS) has not been considered for CP in the literature. The hybrid INS/GNSS methods used for positioning enhancement in standalone nodes cannot be classified as CP because the position-related data are not communicated between at least two independent entities. In this paper, we present a novel CP technique to improve INS-based positioning in vehicular networks. This cooperative inertial navigation (CIN) method can be used to enhance INS-based positioning in difficult GNSS environments, such as in very dense urban areas and tunnels. In the CIN method that is proposed, vehicles communicate their inertial measurement unit (IMU) and INS-based position data with oncoming vehicles traveling in the opposite direction. Each vehicle fuses the received data with those locally observed and the carrier frequency offset (CFO) of the received packets to improve the accuracy of its position estimates. The proposed method is analyzed using simulations and is also experimentally verified. The experimental results show up to 72% improvement in positioning over the standalone INS-based method.
引用
收藏
页码:1370 / 1379
页数:10
相关论文
共 50 条
  • [21] Acoustic Positioning and Navigation System for GNSS Denied/Challenged Environments
    Kapoor, Rohan
    Gardi, Alessandro
    Sabatini, Roberto
    2020 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM (PLANS), 2020, : 1280 - 1285
  • [22] A Kalman Filter-based Doppler-smoothing of Code Pseudoranges in GNSS-Challenged Environments
    Bahrami, Mojtaba
    Ziebart, Marek
    PROCEEDINGS OF THE 24TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS 2011), 2011, : 2362 - 2372
  • [23] Autonomous Vehicle Localization with Prior Visual Point Cloud Map Constraints in GNSS-Challenged Environments
    Lin, Xiaohu
    Wang, Fuhong
    Yang, Bisheng
    Zhang, Wanwei
    REMOTE SENSING, 2021, 13 (03) : 1 - 19
  • [24] Multiantenna GNSS and Inertial Sensors/Odometer Coupling for Robust Vehicular Navigation
    Vagle, Niranjana
    Broumandan, Ali
    Lachapelle, Gerard
    IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (06): : 4816 - 4828
  • [25] Flight Test Setup for Cooperative Swarm Navigation in Challenging Environments using UWB, GNSS, and Inertial Fusion
    de Haag, Maarten Uijt
    Martens, Mats
    Kotinkar, Kevin
    Dommaschk, Jakob
    2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS, 2023, : 286 - 294
  • [26] An Improved Robust Estimation Method for GNSS/SINS under GNSS-Challenged Environment
    Wang, Junwei
    Chen, Xiyuan
    Shi, Chunfeng
    Liu, Jianguo
    2022 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS), 2022, : 79 - 83
  • [27] Cooperative Navigation for an UAV Tandem in GNSS Denied Environments
    Stoven-Dubois, Alexis
    Jospin, Laurent
    Cucci, Davide A.
    PROCEEDINGS OF THE 31ST INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2018), 2018, : 2332 - 2339
  • [28] Lane-Level Localization and Mapping in GNSS-Challenged Environments by Fusing Lidar Data and Cellular Pseudoranges
    Maaref, Mahdi
    Khalife, Joe
    Kassas, Zaher M.
    IEEE TRANSACTIONS ON INTELLIGENT VEHICLES, 2019, 4 (01): : 73 - 89
  • [29] Plug and Play Sensor Fusion for Lane-Level Positioning of Connected Cars in GNSS-Challenged Environments
    Soloviev, Andrey
    Veth, Michael
    Yang, Chun
    PROCEEDINGS OF THE 29TH INTERNATIONAL TECHNICAL MEETING OF THE SATELLITE DIVISION OF THE INSTITUTE OF NAVIGATION (ION GNSS+ 2016), 2016, : 725 - 732
  • [30] Georeferencing in GNSS-Challenged Environment: Integrating UWB and IMU Technologies
    Toth, C. K.
    Koppanyi, Z.
    Navratil, V.
    Grejner-Brzezinska, D.
    ISPRS HANNOVER WORKSHOP: HRIGI 17 - CMRT 17 - ISA 17 - EUROCOW 17, 2017, 42-1 (W1): : 175 - 180