Nonlinear fusion of multiple sensors with missing data

被引:0
|
作者
Housfater, Alon Shalev [1 ]
Zhang, Xiao-Ping [1 ]
Zhou, Yifeng [1 ]
机构
[1] Ryerson Univ, Dept Elect & Comp Engn, Toronto, ON, Canada
关键词
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
We introduce a new algorithm, multiple imputation particle filter, to solve the problem of data fusion with missing data in nonlinear state space models. The new algorithm is then applied to the problem of fusing observations by multiple asynchronous radars. Simulated data is used demonstrate the effectiveness and performance of the fusing algorithm.
引用
收藏
页码:4631 / 4634
页数:4
相关论文
共 50 条
  • [41] Multiple imputation for nonignorable missing data
    Im, Jongho
    Kim, Soeun
    JOURNAL OF THE KOREAN STATISTICAL SOCIETY, 2017, 46 (04) : 583 - 592
  • [42] Multiple imputation for nonignorable missing data
    Jongho Im
    Soeun Kim
    Journal of the Korean Statistical Society, 2017, 46 : 583 - 592
  • [43] An ensemble technique to handle missing data from sensors
    Mohammed, Hussein Syed
    Stepenosky, Nicholas
    Polikar, Robi
    PROCEEDINGS OF THE 2006 IEEE SENSORS APPLICATIONS SYMPOSIUM, 2006, : 101 - 105
  • [44] IMM fusion estimation with multiple asynchronous sensors
    Hu, Yanyan
    He, Xiao
    Zhang, Lan
    Sun, Changyin
    SIGNAL PROCESSING, 2014, 102 : 46 - 57
  • [45] Multiple Imputations Particle Filters: Convergence and Performance Analyses for Nonlinear State Estimation With Missing Data
    Zhang, Xiao-Ping
    Khwaja, Ahmed Shaharyar
    Luo, Ji-An
    Housfater, Alon Shalev
    Anpalagan, Alagan
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2015, 9 (08) : 1536 - 1547
  • [46] Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values
    Wan-Lun Wang
    TEST, 2019, 28 : 196 - 222
  • [47] Mixture of multivariate t nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values
    Wang, Wan-Lun
    TEST, 2019, 28 (01) : 196 - 222
  • [48] When Data Goes Missing: Methods for Missing Score Imputation in Biometric Fusion
    Ding, Yaohui
    Ross, Arun
    BIOMETRIC TECHNOLOGY FOR HUMAN IDENTIFICATION VII, 2010, 7667
  • [49] Optimal Robust H∞ Fusion Filters for Time-Delayed Systems with Multiple Saturation Nonlinear Sensors
    Liu, Meiqin
    Li, X. Rong
    FUSION: 2009 12TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION, VOLS 1-4, 2009, : 1520 - +
  • [50] Multiple imputations for missing data: a simulation with epidemiological data
    Nunes, Luciana Neves
    Klueck, Mariza Machado
    Guimaraes Fachel, Jandyra Maria
    CADERNOS DE SAUDE PUBLICA, 2009, 25 (02): : 268 - 278