Spatiotemporal Registration for Multi-sensor Fusion Systems

被引:0
|
作者
Bu, Shi-zhe [1 ]
Zhou, Gong-jian [1 ]
机构
[1] Harbin Inst Technol, Res Inst Elect Engn, Harbin 150001, Peoples R China
来源
INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTER SCIENCE (AICS 2016) | 2016年
基金
中国国家自然科学基金;
关键词
Spatiotemporal registration; Data fusion; Unscented Kalman filter (UKF); State augmentation method;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A method of online sensor fusion with spatially and temporally misaligned sensors is considered in this paper. A spatiotemporal registration mode is developed for sensor alignment, and augment the target state vector with spatiotemporal bias. An unscented Kalman filter (UKF) is used to fuse and register these sensors, then the target state estimation as well as the spatial and temporal bias estimation can be obtained simultaneously. Simulations show that the proposed algorithm not only can align these sensors properly with both spatial and temporal bias, but can also obtain accurate fused tracks.
引用
收藏
页码:333 / 339
页数:7
相关论文
共 50 条
  • [31] Multi-sensor panorama fusion and visualization
    Scheibe, Karsten
    Klette, Reinhard
    IMAGING BEYOND THE PINHOLE CAMERA, 2006, 33 : 185 - +
  • [32] A Maximum Likelihood Approach to Joint Registration, association and Fusion for Multi-Sensor Multi-Target Tracking
    Chen, Siyue
    Leung, Henry
    Bosse, Eloi
    FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2009, : 686 - +
  • [33] Multi-sensor detection and fusion technique
    Bhargave, Ashish
    Arnbrose, Barry
    Lin, Freddie
    Kazantzidis, Manthos
    MULTISENSOR, MULTISOURCE INFORMATION FUSION: ARCHITECTURES, ALGORITHMS, AND APPLICATIONS 2007, 2007, 6571
  • [34] Fusion of noisy multi-sensor imagery
    Mishra, Anima
    Rakshit, Subrata
    DEFENCE SCIENCE JOURNAL, 2008, 58 (01) : 136 - 146
  • [35] An introduction to multi-sensor data fusion
    Llinas, J
    Hall, DL
    ISCAS '98 - PROCEEDINGS OF THE 1998 INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS, VOLS 1-6, 1998, : E537 - E540
  • [36] Multi-Sensor Measurement and Data Fusion
    Liu, Zheng
    Xiao, George
    Liu, Huan
    Wei, Hanbing
    IEEE INSTRUMENTATION & MEASUREMENT MAGAZINE, 2022, 25 (01) : 28 - 36
  • [37] Survey of multi-sensor image fusion
    Yang, Aolei, 1600, Springer Verlag (461):
  • [38] MULTI-SENSOR FUSION FOR VIDEO SEGMENTATION
    Scheuermann, Bjorn
    Rosenhahn, Bodo
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2014, 28 (07)
  • [39] Survey of Multi-sensor Image Fusion
    Wu, Dingbing
    Yang, Aolei
    Zhu, Lingling
    Zhang, Chi
    LIFE SYSTEM MODELING AND SIMULATION, 2014, 461 : 358 - 367
  • [40] A theoretical perspective in multi-sensor fusion
    Wu, XZ
    Li, SY
    SENSORS AND CONTROLS FOR INTELLIGENT MACHINING AND MANUFACTURING MECHATRONICS, 1999, 3832 : 163 - 169