Terrain Matching Localization for Underwater Vehicle Based on Gradient Fitting

被引:2
|
作者
Gao, Jiaqi [1 ]
Peng, Dongdong [1 ]
Zhou, Tian [1 ]
Wang, Tianhao [1 ]
Xu, Chao [1 ]
机构
[1] Harbin Engn Univ, Coll Underwater Acoust Engn, Acoust Sci & Technol Lab, Harbin, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
NAVIGATION;
D O I
10.1155/2018/3717430
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Terrain matching positioning is a promising method to overcome the problem that the inertial navigation error of the underwater vehicle accumulates over time. In the conventional terrain matching method, all measurement points are commonly used for matching and positioning. However, this method fails to be taken into a balanced consideration on both the computation complexity and the positioning accuracy. To reduce the computation and ensure the accuracy at the same time, an improved terrain matching method based on the gradient fitting is proposed in this paper. In the method, the gradient distributions of multiple terrain regions are firstly analyzed. Then, normal distribution is used to fit them, and according to the distribution, points with larger gradient values are selected as matching points. Finally, minimum absolute difference matching is chosen to match for positioning. Simulation results using multibeam sonar show that the improved terrain matching localization method not only reduces the computational complexity but also improves the accuracy of positioning.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Terrain matching localization for hybrid underwater vehicle in the Challenger Deep of the Mariana Trench
    Wang, Jian
    Tang, Yuan-gui
    Chen, Chuan-xu
    Li, Ji-xu
    Chen, Cong
    Zhang, Ai-qun
    Li, Yi-ping
    Li, Shuo
    FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING, 2020, 21 (05) : 749 - 759
  • [2] Terrain matching localization for hybrid underwater vehicle in the Challenger Deep of the Mariana Trench
    Jian Wang
    Yuan-gui Tang
    Chuan-xu Chen
    Ji-xu Li
    Cong Chen
    Ai-qun Zhang
    Yi-ping Li
    Shuo Li
    Frontiers of Information Technology & Electronic Engineering, 2020, 21 : 749 - 759
  • [3] Particle filter underwater terrain-aided navigation based on gradient fitting
    Zhou, Tian
    Wang, Tianhao
    Gao, Jiaqi
    Guo, Qijia
    Yan, Zhenyu
    MEASUREMENT SCIENCE AND TECHNOLOGY, 2022, 33 (10)
  • [4] Localization of a Drifting Underwater Vehicle Using a Terrain-Based Particle Filter
    Casagrande, David
    Krasnosky, Kristopher
    Roman, Chris
    OCEANS 2019 MTS/IEEE SEATTLE, 2019,
  • [5] Segmentation of bathymetric profiles and terrain matching for underwater vehicle navigation
    Lucido, L
    Pesquet-Popescu, B
    Opderbecke, J
    Rigaud, V
    Deriche, R
    Zhang, Z
    Costa, P
    Larzabal, P
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 1998, 29 (10) : 1157 - 1176
  • [6] Exploiting Deep Matching and Underwater Terrain Images to Improve Underwater Localization Accuracy
    Zhang, Feng
    Bian, Hongyu
    Ge, Wei
    Wei, Mingzhe
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [7] Research on Performance of Terrain Matching Algorithm for Underwater Autonomous Vehicle Based on Particle Filter
    Jian, Shen
    Lu, Xiong
    Ning, Ba
    2019 5TH INTERNATIONAL CONFERENCE ON MECHANICAL ENGINEERING AND AUTOMATION SCIENCE (ICMEAS 2019), 2019, 692
  • [8] A Huber based Unscented Kalman Filter Terrain Matching Algorithm for Underwater Autonomous Vehicle
    Xiong, Lu
    Shen, Jian
    Bi, Xiaowen
    PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2019), 2019,
  • [9] Model Based Vehicle Localization for Urban Traffic Surveillance Using Image Gradient Based Matching
    Zheng, Yuan
    Peng, Silong
    2012 15TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2012, : 945 - 950
  • [10] Robust underwater terrain matching navigation based on M estimation
    Zhang, Kai
    Zhao, Jianhu
    Zhang, Hongmei
    Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2015, 40 (04): : 558 - 562